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Color image segmentation thesis

Each region is of a signi cant size compared to the image size. Rafiqul Islam (Advisor) Dr. color image segmentation thesis http://moneyreign.com/esl-research-proposal-proofreading-services-au power of personal computers is increasing rapidly, and PCs can be used to process color images [6]. Govardhan & Dr. Heightmap generation for printed circuit boards (PCB) using laser triangulation for pre-processing optimization in industrial recycling applications. Abstract.

The image regions are obtained using a segmentation technique and a set of features is extracted from these segments. color image segmentation thesis We decompose the global energy optimization formulation that typically models the soft color segmentation task into three sub-problems that can be implemented with computational efficiency and scalability A new quantitative image segmentation evaluation procedure is introduced to assess the performance of both algorithms. When calling the plugin,. segmentation refers to the process of partitioning a digital image into multiple segments (sets of pixels, also known as superpixels). This is essential to ensure the spacial consistency of each region. Active http://digitalmagic.ca/wp-content/plugins/formcraft/file-upload/server/php Contours and Image Segmentation: The Current State of the Art .

Saiful Azad (External) Dr. The simplest form of segmentation is binarization.. Our segmentation algorithm consists of generic machinery for transforming the output of any scope and limitations in research paper sample contour detector into a hierarchical region tree. SIOX is a plugin designed to segment 2D color images. Segmentation could therefore be seen as a computer vision problem. Ideally, classes with similar characteristics correspond color image segmentation thesis to similar objects in an image.

Free research papers-image Segmentation. Color Image Edge Detection and Segmentation: A Comparison of the Vector Angle and the Euclidean Distance Color Similarity Measures by Slawomir Bogumil Wesolkowski A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree color image segmentation thesis of Master of Applied Science in Systems Design Engineering Waterloo, Ontario. Md. Fingerprint Identification System in Banking Transactions Bachelor's Thesis in Mathematics and Computer Science University of Science, VNU-HCMC, Vietnam, 2009.superpixels of ….

This contains the MATLAB code for Tumor Segmentation from Brain MRI images. Image segmentation can be classified to boundary representation and regional representation. III. Once a joint probability model is available, a number of applications are possible Image segmentation is important part in many signal processing technique and its applications. The resulting sets, called regions, are defined based on visual properties extracted by local features A multi-region image segmentation method for color remote sensing images has been proved in the thesis, which will make preprocessing to color remote images firstly, and then split the target regions combining with K-mean clustering algorithm and region growing segmentation algorithm This paper researches on methods of the color image segmentation method of Lingwu long jujubes based on the maximum entropy to achieve the accuracy of image segmentation and improve accuracy of machine recognition. Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches Spatial Finite Non-Gaussian Mixtures for Color Image Segmentation. This is essential to ensure the spacial consistency of each region. However, the SIOX algorithm makes uses color information, so it is expected to work better on real RGB images First, we show the sensed images (top row) with marked contour of segmented disc (orange) and gene expression (red) followed by visualization of the segmented discs (middle row) color image segmentation thesis and segmented gene expressions (bottom row).

These features form a visual description of the image regions and are used in learning the relationship between them and the words. For the acquisition of the image, color image segmentation thesis a sensor array is used This thesis investigates two fundamental problems in computer vision: contour detection and image segmentation. A significant contribution of this thesis is that we. A version of watershed algorithm for color image segmentation Md. If the image is not RGB color, it can be converted to RGB using the command Image › Type › RGB Color.

Every pixel in a region color image segmentation thesis is similar in some characteristics such as color, intensity, or texture. Keywords: image segmentation, clustering analysis, mean shift, Hierarchical clustering 1. A comprehensive survey of basic image segmentation techniques is given. superpixels of …. …. Adjacent regions are significantly different with respect to the same characteristics [1]. Habibur Rahman (11-94853-2) Master’s Thesis Presentation and Defense Thesis Committee : American International University-Bangladesh June, 2013 1 Prof. When clustering the pixels in a color image, an important aspect of the segmentation method is the color space, from which the color features are inferred.

Segmentation color image thesis

Three noise classes represented by red, green, and blue for clarity (c) Superpixel. Compared to the gray scale images, color images include not only the brightness but also the color information, such as hue and saturation MEDICAL IMAGE SEGMENTATION by FELICIA S. This thesis introduces a new image segmentation implementation that uses the bee algorithm as an optimization tool in the Markovian framework. The dataset contains T1-weighted contrast-enhanced images with three kinds of brain tumor His research interests are concentrated on computer vision and pattern recognition including visual tracking, robust statistics, object detection, video segmentation, model fitting, optical flow calculation, 3D structure from motion, image segmentation and related fields. Latest topics in digital image processing for research and thesis are based on these algorithms Jul 08, 2013 · A version of watershed algorithm for color image segmentation 1. intensity, color, and quality. Each region is a closed connected component. Notice how easily you can visually distinguish these colors from one another. These parts normally correspond to something that humans can easily separate and view as individual objects In this thesis, we address these issues and propose novel unsupervised methods for 3D image clustering and joint color and depth image segmentation. Reign based segmentation involves the examination of neighboring pixels of initial seed points and verifies whether the pixel neighbors should be added to the region This thesis color image segmentation thesis proposes a multi-resolution region preserving segmentation ap-proach on color images. Segmentation in the thesis: segmentation: image made an appearance to get includes a wavelet according to image domain independent partition an essay Jul 29, 2016 · The MRF model is used for color image segmentation in the framework. visualization of approximately 6 6 pixels each, (d) LLPD segmentation using.

03. Color image segmentation approaches can be broadly classifled in: † edge and line oriented segmentation, † region growing methods, and † clustering. Image segmentation is an important aspect of the human visual perception comparing the consumer-quality pill image segmentation masks to the high quality reference pill image masks. Most tumor segmentation methods are based on grayscale values of the medical images. color image segmentation thesis This thesis presents a new segmentation method called the Medical Image Segmentation Technique (MIST), used to extract an anatomical object of interest from a stack of sequential full color, two-dimensional medical images from the Visible Human dataset 1 Segmentation of the plant from background objects a challenging is task due to the fact that background objects often closely resemble the plant in color. The segmentation of color images (RGB) is extremely challenging, due to the variety of possible color intensities and the presence of three color channels, unlike gray images which have only a. The goal of segmentation is typically to locate certain objects of interest which may be depicted in the image. Baswaraj, Dr. a small set of image regions which are coherent in color and texture space. This gradient-based segmentation method is initialized by a vector gradient calculation on the full resolution input image in the CIE L*a*b* color space these systems typically average the red, green, and blue color channels together to form a black and white image.

2. Brain Tumor Segmentation in MRI Images. An image segmentation algorithm is applied to each PIMP, and then the union of the segmented PIMPs is mapped back to the 3D point cloud A color image segmentation algorithm is proposed by generating superpixels using the Simple Linear Iterative Clustering (SLIC) algorithm and merging the superpixels by color image segmentation thesis thresholding the region adjacency graphs.. In our case we are interested in color image segmentation, which means that color values are used to measure …. Each representation is identification of homogeneous regions or contours of local inhomogeneity, respectively . Image segmentation is an essential step in image analysis because it determines the quality of future interpretation of the component image and substantially influences the decision. Formation of Digital Images. Adaptive Edge Synthesis for Image Segmentation Using Color and Depth Images A thesis Submitted to the Graduate School of UNIST in partial fulfillment of the requirements for the degree of Master of Science Tae-Hui Yun 06. 4.

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Which have bases as color, pixel in an image. The method proposed in this thesis adds color information to the original values of the image. Faculty of Engineering, OU, Hyderabad, AP, India . Then, color image segmentation thesis a color- quantized image can be obtained by replacing the color of each pixel with its most similar color in the color palette. In this study we present a fast unsupervised segmentation method of color images based on the 3D compact histograms. The. Thesis On Color Image Segmentation - esl lesson resume - professional mba blog post assistance. Given a certain color space, there are also various ways to compute the distance be-. Color object segmentation techniques, such as GrabCut etc., available in the literature,. In this way, an initial segmentation result is obtained Segmentation subdivides an image into its constituent regions or objects. Also which algorithm is robust and works well is depends on the type of image [3]. This Bachelor thesis will examine the use of the method of Particle Swarm Optimization (PSO) applied to the task of clustering the pixels of an image.

The. These parts normally correspond to something that humans can easily separate and view as individual objects Jun 11, 2013 · The simplest case is that the cluster count means the color count and the cluster centers are the color values. In other words, if you have an RGB image with millions of colors, after K-means clustering with value 20, you will have the image converted to a version which only has 20 colors. Most techniques use either the RGB or the hue, saturation, intensity (HSI) systems It is also called as a pixel-based image segmentation method as it includes the color image segmentation thesis selection of initial seed points. SIOX is a plugin designed to segment 2D color images. In this thesis, we propose a fast unsupervised multiresolution color image segmentation algorithm which takes advantage of gradient information in an adaptive and progressive framework. Thesis On Color Image Segmentation, example office manager resume, brokerage business plan template, essays on the scarlet ibis by james hurst. Segmentation is also.

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In this project, a fast threshold selection method based algorithm is implemented to speed up the original MCE threshold method in image segmentation. Edge and line oriented segmentation approaches work on image data either through in-. To this aim, we consider image normals as the prominent feature from 3D image and cluster them with methods based on finite statistical mixture models Find the link at the end to download the latest thesis and research topics in Digital Image Processing. Image segmentation is a vital field in image. This so-called “blobworld” representation is based on segmentation using the Expectation-Maximization algorithm on combined color and texture features. by Hanzi Wang. This thesis proposes a multi-resolution region preserving segmentation ap-proach on color color image segmentation thesis images. We propose an energy formulation for producing compact layers of homogeneous colors and a color refinement procedure, as well as a method for automatically estimating a statistical color model from an image. There are many method for segmentation: watershed based segmentation, split and merge, region growing, threshold based segmenation etc,. These include reversible jump mechanism from MCMC methodology For gray images, the segmentation is carry out on the basis of image gray levels where the brighter part of an image is object and darker is background.

Visualization of approximately 6 6 pixels each, (d) LLPD segmentation using. Jul 08, 2013 · It is a process to divide the digital image into homogeneous and different meaningful regions The main goal of image segmentation is to cluster of pixels in the relevant regions It is used to recognize color image segmentation thesis similar regions and grouping the similar visual objects Property like grey level, color, intensity, texture, shape, depth or motion from the digital image Image …. By dividing an image into segments, you can process only the important segments of the image instead of processing the entire image of image segmentation is to locate objects and boundaries in images, which results in a set of regions that communally cov-er the entire image. JONES (Under the Direction of Hamid Arabnia) ABSTRACT The National Library of Medicine’s Visible Human Project is a digital image library containing full color anatomical, CT and MR images representing an adult male and female thesis on color, thesis on color blindness, thesis on colorectal cancer, thesis on color image segmentation, thesis on color purple, thesis on columbine school shooting, thesis on commerce, thesis on commerce and management, thesis on commerce topics, thesis on commercial banks. Each region is of a signi cant size compared to the image size. The algorithm is based on Morphological operations, so is fast enough in processing. Given a certain color space, there are also various ways to compute the distance be-. THE STUDY OF COLOR IMAGE SEGMENTATION Image segmentation is the process of separating or grouping an image into different parts. He is a Senior Member of the IEEE processing. The experiments show that the new proposed method performs faster than the existing implementation methods with about the same segmentation … Author: Vehbi Dragaj Publish Year: 2016 [PDF] 'Eulllhlll - DTIC https://apps.dtic.mil/Dtic/Tr/Fulltext/U2/A274027.pdf as well as background information on the form segmentation techniques used in this thesis.

Abstract In image analysis, segmentation is the partitioning of a digital image into multiple regions (sets of pixels), according to some homogeneity criterion. Each region is a closed connected component. Thus, only. These include reversible jump mechanism from MCMC methodology probabilistically. [7] can be replicated for color images May 26, 2012 · Splitting an input image into connected sets of pixels is color image segmentation thesis the purpose of image segmentation. The dataset contains T1-weighted contrast-enhanced images with three kinds of brain tumor Abstract— Image segmentation is an important and difficult task of image processing and the consequent tasks including object detection, feature extraction, object recognition and categorization depend on the quality of segmentation process Therefore image segmentation for color images is totally different from gray scale images, e.g., content based image retrieval[1], [2]. According to law between the color of Lingwu long jujubes and characteristic of environment, starting from the hue information, this paper is first …. The problem of segmentation is a well-studied one in literature and there are a wide variety of approaches that are used This thesis proposes a multi-resolution region preserving segmentation ap-proach on color images. First, we show the sensed images (top row) with marked contour of segmented disc (orange) and gene expression (red) followed by visualization of the segmented discs (middle row) and segmented gene expressions (bottom row). Sefidpour, Ali (2011) Spatial Finite Non-Gaussian Mixtures for Color Image Segmentation. Clustering based colour image segmentation phd thesis proposal Partners ph. Compared to the gray scale images, color images include not only the brightness but also the color information, such as hue and saturation The fixed angular acquisition pattern of the scan permits creation of 2D structured panoramic image maps (PIMPs) representing various subsets of the data including normal, intensity, range, and RGB color.

Also which algorithm is robust and works well is depends on the type of image [3]. Only the cellular anatomy channel is used for semantic and instance segmentation Torsten Koch, Matthias Breier and Wei Li. The L*a*b* color space is derived from the CIE XYZ tristimulus values A fully automated method for content-based color image retrieval is developed to. Image segmentation: To humans, an image is not just a random collection of pixels; it is a meaningful arrangement of regions and objects. In order to resolve the problems of handling 3D histograms and to palliate the defects of the marginal and bi-marginal approaches, the use of the 3D compact histogram to accomplish classification in the color space RGB proved to be necessary Robust Statistics for Computer Vision:Model Fitting, Image Segmentation and Visual Motion Analysis. Homogeneity can be measured against some characteristics. Masters thesis, Concordia University In this thesis a color pre-processing method for segmentation is presented. Naturally, the choice of the feature space determines the statistical image model Thesis Title: Tracking Color Objects in Real Time Color has been widely used color image segmentation thesis in machine-based vision systems for tasks such as image segmentation, object recognition and tracking. P. The focus of this thesis is to develop novel deep learning methods for the segmentation of natural images and of 2D and 3D medical images Color clustering was examined using the k-means (based on the Euclidean distance) and Mixture of Principal Components (based on the vector angle) algorithms. We present new state-of-the-art algorithms for both of these tasks. The property of a pixel in an image and information of pixels near to that pixel are two basic parameters for any image segmentation.

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The goal of image segmentation is to assign each pixel to a group or class with similar characteristics. k-mean clusteling algorithm is used and a saturated distance color image segmentation thesis is proposed to discriminate. Then, a color- quantized image can be obtained by replacing the color of each pixel with its most similar color in the color palette. May 26, 2012 · In the context of Bayesian color image segmentation, various aspects of sampling from the posterior distributions to estimate the color distribution from MGMM and the label field, using different move types are also discussed. SEGMENTATION ALGORITHMS AND COLOR CONSTANCY ALGORITHMS USING WORD PREDICTION by Prasad Gabbur _____ A Thesis Submitted to the Faculty of the DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING In Partial Fulfillment of the Requirements For the Degree of MASTER OF SCIENCE In the Graduate College THE UNIVERSITY OF ARIZONA 2 0 0 3. Only the cellular anatomy channel is used for semantic and instance segmentation for k = 4 segments, with the background class represented by average color and. The resulting segmentation should have the following properties: 1. We identify a set of requirements that soft color segmentation methods have to fulfill, and present an in-depth theoretical analysis of prior work The traditional robust methods generally assume that the data of interests (inliers) occupy a majority of the whole data.

Thus, only. The accuracy of segmentation rate is up to 89.60% Variational Image Segmentation and Curve Evolution on Natural Images by Baris Sumengen The primary goal of this thesis is to develop robust image segmentation meth-ods based on variational techniques. If the image is not RGB color, it can be converted to RGB using the command Image › Type › RGB Color. Brain Tumor Segmentation in MRI Images. Each region is of a signi cant size compared to the image size. Dr. It is a major problem, difficult and for which there is no universal solution Image segmentation is an essential procedure in many applications of image processing. In this. extract color and shape content of an image. Our main aim is to find various segments inn an image on color image segmentation thesis basis of its feature The literature on color image segmentation is not that rich as it is for gray tone images. Image segmentation refers to partitioning an image into different regions that are homogeneous with respect to some image feature.

Hence, the H, S and I features also exhibit the clustering and persistence properties to some extent. for k = 4 segments, with the background class represented by average color and. A new quantitative image segmentation evaluation procedure is introduced to assess the performance of both algorithms color image segmentation thesis One of the most important problems in image processing and analysis is segmentation [12, 13, 17]. Segmentation algorithms are usually based on either. Image segmentation is important part in many signal processing technique and its applications. Section 2 presents a K-means++ clustering approach for nuclei segmentation in digitized histology images. In this work, we have used region. The segmentation operation is then performed on the black and white image. This results in a novel framework for automatic and high-quality soft color segmentation, which is efficient, parallelizable, and scalable The final representative color set is called the color palette of the input image. We show that the resulting decomposition serves as an effective intermediate image representation, which can be utilized for performing various, seemingly unrelated image manipulation tasks.

The objects and background of gray level images can be easily identified, but the process becomes more complicated for color or textured images.. In particular, we will examine if the results of the so-called MEPSO algorithm of Das et al. III. The function of segmentation is to dividing an image into color image segmentation thesis its basic and disjoint subregions, which are identical according to - their property, e.g. It offers several significant advantages over typical color object segmentation would involve a conversion of these values to some color model. The basic hypothesis of this research is that the use of full color imagery to locate defects will. 2. There also exits a variety of images: natural scenes, paintings, etc. By D.

Location based Active Contour Model for Object Segmentation from Natural Color Images Master's Thesis in Computer Science Chonnam National University, Gwangju, South Korea, 2012. to a certain label based on similar attributes, such as texture, color, intensity, or distance metrics. Md. THE STUDY OF COLOR IMAGE SEGMENTATION Image segmentation is the process of separating or grouping an image into different parts. Beatriz Díaz Acosta Chapter 3: Character Segmentation 43 The 1976 CIE L*a*b* color coordinate system was developed to represent equal changes in the chromaticity coordinates for equal noticeable changes in perceived hue and saturation of …. Quantitative and qualitative results on many color images (artificial, staged scenes and natural scene images) indicate good edge detection performance using a vector version of the Sobel operator on the h1h2h3 color space Color Image Segmentation. Abstract - Image segmentation is a fundamental task in image analysis responsible for partitioning an image into multiple sub-regions based on a desired feature.. 2.2 Color Segmentation The first step in developing a color segmentation scheme is to determine in which color coordinate system to work. Digital image processing is the process of using computer algorithms to perform image processing on digital images. The method proposed in this thesis adds color information to the original values of the image. Introduction Currently the clustering method often used for segmenting large-scale images performs pre-treatment of images, which can be implemented with color image segmentation thesis less complicated. Despite the large variations of ….

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An explanation of is-sues related to selecting a color space for a particular purpose and a review of the most common color spaces is included. In this way, an initial segmentation result is obtained comprises image acquisition, segmentation, object recognition, and feature classification is described. In this thesis a color pre-processing method color image segmentation thesis for segmentation is presented. In many cases image segmentation remains an unsolved problem [16, 17, 18]. User Manual. The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze The H, S and I values at coarser scales are computed as the mean of the corresponding four values at the next higher- resolution scale. In image analysis, however, the data is often complex and several instances of a model are simultaneously present, each accounting for a relatively small percentage of the data points His research interests are concentrated on computer vision and pattern recognition including visual tracking, robust statistics, object detection, video segmentation, model fitting, optical flow calculation, 3D structure from motion, image segmentation and related fields. He is a Senior Member of the IEEE Image Segmentation involves converting an image into a collection of regions of pixels that are represented by a mask or a labeled image. The L*a*b* color space (also known as CIELAB or CIE L*a*b*) enables you to quantify these visual differences. three noise classes represented by red, green, and blue for clarity (c) Superpixel. In this thesis, we assume that the inliers occupy a relative majority of the data, by which it is possible that a robust estimator can tolerate more than 50% outliers. The development of the computer vision system that.

Each region is a closed connected component. The result of image segmentation is a set of segments that collectively cover the entirety of an image. Take a look at the histograms below.. When clustering the pixels in a color image, an important aspect of the segmentation method is the color space, from which the color features are inferred. Image segmentation is a basic task, responsible for the separating process. This paper critically reviews and summarizes some color image segmentation thesis of these techniques. The tex- ture features we use for the segmentation arise from a new approach to texture description and scale selection May 26, 2012 · Splitting an input image into connected sets of pixels is the purpose of image segmentation. Image segmentation is one of the funda-mental problems in image processing and computer vision. The remainder of this thesis is organized as follows. A simple example of segmentation is thresh-olding a grayscale image with a fixed threshold t: each pixel p is assigned to one of two classes, P 0 or P.

Image segmentation is a process by which image pixels are grouped into homogenous groups, causing the image to be segmented or in color image segmentation thesis other words to be split into homogenous regions known as segments. Thesis On Color Image Segmentation - esl lesson resume - professional mba blog post assistance Your Peers Got an Edge Your classmates may already have an advantage over you – just because they are getting online homework help – and you still haven't In this method, the use of multi- Gaussian thresholding method for color image segmentation get quick color face candidate regions ; window color to be detected if more than a certain percentage , then use the cascade AdaBoost classifier to detect , or direct contracting for non- …. 2. The property of a pixel in an image and …. between two color points in the HSV color space According to the image gray level, image segmentation can be divided into gray scale image segmentation and color image segmentation. Premchand . In: Proceedings of the 11th IEEE International Conference on Industrial Informatics (INDIN). A multi-region image segmentation method for color remote sensing images has been proved in the thesis, which will make preprocessing to color remote images firstly, and then split the target regions combining with K-mean clustering algorithm and region growing segmentation algorithm Questions concerning the deposit of theses in Spectrum can be directed to the Thesis Office, at 514-848-2424 ext. The soft color segments can be overlayed to give the original image, providing effective intermediate representation of an image. Most tumor segmentation methods are based on grayscale values of the medical images.

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That is, segmentation should stop when the objects of interest in an application have been isolated. Segmentation algorithms for monochrome images generally are based on one of …. Our first focus is representing images as a mixture of main colors in the scene, by estimating soft segments of homogeneous colors Segmentation is a task of division. Ali Sefidpour A Thesis in The Concordia Institute for Information Systems Engineering Presented in Partial Fulfillment of the Requirements for the Degree of Master of Applied Science (Quality Systems Engineering) at Concordia University Montreal, Qu´ ´ebec, Canada August 2011 There are three colors: white, blue, and pink. Section 3 presents a deep learning approach for nuclei segmentation According to the image gray level, image segmentation can be divided into gray scale image segmentation and color image segmentation. Your Peers Got an Edge tion of an object in a color image. A. 3802 or at thesis@alcor.concordia.ca For other questions please contact Spectrum editors at lib-spectrum@concordia.ca. The resulting sets, called regions, are defined based on visual properties extracted by local features By comparing the segmentation effect with artificial method of the 30 Lingwu long jujubes images, it proves that the color image segmentation method of Lingwu long jujubes based on the maximum entropy has good effect to extract the object region. In this thesis, we approach the soft segmentation problem from two complementary properties of a photograph. The resulting segmentation should have the following properties: 1. color image segmentation thesis

A color segmentation color image segmentation thesis algorithm based on the. This contains the MATLAB code for Tumor Segmentation from Brain MRI images. May 26, 2012 · In the context of Bayesian color image segmentation, various aspects of sampling from the posterior distributions to estimate the color distribution from MGMM and the label field, using different move types are also discussed. 2013 Month/Day/Year of submission Approved by Major Advisor Jae-Young Sim. The algorithm is based on Morphological operations, so is fast enough in processing. Thus, only. The resulting segmentation should have the following properties: 1. Disregarding partially occluded leaves is also a challenging problem, because leaves that are from the same plant are often of …. Therefore image segmentation for color images is totally different from gray scale images, e.g., content based image retrieval[1], [2].

Firstly, the image is captured by a camera using sunlight as the source of energy. However, the SIOX algorithm makes uses color information, so it is expected to work better on real RGB color image segmentation thesis images. The major merit of the thesis is the development of algorithms that localize the end of a log from a camera image, and detect if there are visible defects on the surface of the log end employed on color image and medical image segmentation. This technique deals with the complex problem of segmentation of an object which contains holes in it, and in addition, the color distribution of a part of the object is similar to that of the background. In particular their application for the segmentation of color images is discussed. The final representative color set is called the color palette of the input image. This is essential to ensure the spacial consistency of each region.



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