What is Image Segmentation

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Image segmentation is a technique of dividing a digital image into multiple segments so as to simplify an image. This simplification helps in a study of images for further analysis. Learn more in: Improved Lymphocyte Image Segmentation Using Near Sets for ALL Detection

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The process of partitioning a digital image into multiple segments (sets of pixels) for the purpose to simplify or change the representation of an image into something that is more meaningful and easier to analyze. Learn more in: Melanocytic Lesions Screening through Particle Swarm Optimization

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A process consists of subdividing an image into its constituent parts and extracting these parts of interest (objects) from the image. Learn more in: A Review of Image Segmentation Evaluation in the 21st Century

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A process consists of subdividing an image into its constituent parts and extracting these parts of interest (objects) from the image. Learn more in: A Study of Image Engineering

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A collection of image pixels, similar to one another within the same segment, dissimilar to the objects in other segments with respect to some features. Learn more in: Multilevel Image Segmentation by a Multiobjective Genetic Algorithm Based OptiMUSIG Activation Function

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This is an important image processing task that partitions the image into meaningful regions. Learn more in: Segmentation Methods in Ultrasound Images

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Is the process of partitioning a digital image composed by pixels into multiple regions of interest. Learn more in: A Survey of Bayesian Techniques in Computer Vision

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A collection of image pixels, similar to one another within the same segment, dissimilar to the pixels in other segments with respect to some features. Learn more in: Multilevel and Color Image Segmentation by NSGA II Based OptiMUSIG Activation Function

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Image segmentation is a technical process which can divide an image into regions with certain and special characteristics and extract the objectives interested from them. Classic image segmentation is to construct a differential operator that is sensitive to pixel gray-level’s step changing, such as Laplace operator, Roberts gradient operator, Sobel gradient operator, etc. Learn more in: Immune Programming Applications in Image Segmentation

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A step in most image processing applications, where the image is processed to extract a given object. Learn more in: On the Use of Artificial Intelligence Techniques in Crop Monitoring and Disease Identification

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A process consists of subdividing an image into its constituent parts and extracting these parts of interest (objects) from the image. Learn more in: Half Century for Image Segmentation

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Extracting various levels of information (colours, gradient, textures etc) from an image. Learn more in: Automated Building Process Monitoring

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A process consists of subdividing an image into its constituent parts and extracting these parts of interest (objects) from the image. Learn more in: Image Segmentation in the Last 40 Years

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The purpose of image segmentation is to partition an image into meaningful regions with respect to a particular application. The segmentation is based on measurements taken from the image and might be grey level, colour, texture, depth or motion Learn more in: Semi-Automatic Vertebra Segmentation

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Partition of an image into not overlapping, constituent regions that are homogeneous with respect to some characteristic. Ideally, a segmentation method finds sets of points that correspond to distinct structures or regions of interest in the image. Learn more in: The Relevance of Computer-Aided-Diagnosis Systems in Microscopy Applications to Medicine and Biology

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Image segmentation is a method to individually identify each constituting segments in an image. Learn more in: An Advanced Approach to Detect Edges of Digital Images for Image Segmentation

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Partitioning image into different clusters. Learn more in: Importance of Deep Learning Models in the Medical Imaging Field

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It is the process of partitioning a digital image into multiple segments on the basis of their similarities. Learn more in: Quantum Inspired Swarm Optimization for Multi-Level Image Segmentation Using BDSONN Architecture

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Process of partitioning a digital image into object(s) and background. The goal of segmentation is to simplify the representation of an image into something that is more meaningful and easier to analyze. Learn more in: Image Segmentation Methods

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A process consists of subdividing an image into its constituent parts and extracting these parts of interest (objects) from the image. It is a fundamental step and a critical task in image analysis. Learn more in: Image Segmentation Evaluation in this Century

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Image segmentation subdivides the image into constituent features with certain dissimilarity properties using the measuring metrics from each other. Learn more in: Use of PCA Solution in Hierarchy and Case of Two Classes of Data Sets to Initialize Parameters for Clustering Function: An Estimation Method for Clustering Function in Classification Application

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Is the process of partitioning a digital image into multiple segments (sets of pixels, also known as super-pixels). Learn more in: Image Processing and Post-Data Mining Processing for Security in Industrial Applications: Security in Industry

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Is the process of clustering or partitioning a digital image features into multiple sets of pixels to simplify or change the representation of an image into something, which understandable to more meaningful and easier to identify objects or other relevant information in digital formats. Learn more in: Image Data Mining Based on Wavelet Transform for Visualization of the Unique Characteristics of Image Data

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The process of partitioning a digital image into multiple homogenous segments in order to simplify/modify the representation of an image for further analysis; typically used to locate objects and boundaries within an image. Learn more in: A Survey of Approaches for Estimating Meteorological Visibility Distance Under Foggy Weather Conditions

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A process in which an image is partitioned into multiple regions (sets of pixels/voxels in 2D/3D) based on a given criterion. These regions are nonoverlapping, homogeneous with respect to some characteristics such as intensity or texture. If the boundary constraint of the region is removed, the process is defined as classification. Learn more in: 3D and 4D Medical Image Registration Combined with Image Segmentation and Visualization

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Partitioning images into regions which are homogeneous with respect to some criteria that concern color, intensity, or texture. Learn more in: Fast and Robust Fuzzy C-Means Algorithms for Automated Brain MR Image Segmentation

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Segmentation is the method that is dividing an image into separate regions containing each pixel with similar attributes. To be meaningful and useful for image analysis and interpretation, the regions should strongly relate to depicted objects or features of interest. Learn more in: Active Contour Model for Medical Applications

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Is the process of partitioning a digital image into multiple segments represented by sets of pixels. Learn more in: Intelligent Processes in Automated Production Involving Industry 4.0 Technologies and Artificial Intelligence

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In computer vision, image segmentation is the process of partitioning a digital image into multiple segments. Learn more in: Automation in Sputum Microscopy: A Hybrid Intelligent Technique in Diagnostic Device Automation

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Refers to the process of partitioning the digital image into its constituent regions or objects so as to change the representation of the image into something that is more meaningful and easier to analyze. Learn more in: Computational Intelligence for Pathological Issues in Precision Agriculture

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This technique is a pre-processing activity that is carried out in image processing. This partitions the image into multiple segments and identifies the different bounded regions present in the image using computer algorithms. Learn more in: Recommendation of Crop and Yield Prediction by Assessing Soil Health From Ortho-Photos

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A process consists of subdividing an image into its constituent parts and extracting these parts of interest (objects) from the image. Learn more in: A Critical Overview of Image Segmentation Techniques Based on Transition Region

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It is the process of dividing an image into multiple segments. The aim is to get more meaningful information and easier for analyzing. Learn more in: Deep Learning Techniques for Prediction, Detection, and Segmentation of Brain Tumors

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Dividing the image into several homogeneous regions. Learn more in: Applications of Image Processing in Laparoscopic Surgeries: An Overview

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It’s the process of partitioning the digital image into multiple segments otherwise, set of pixels. Learn more in: Recent Trends in Spatial Data Mining and Its Challenges

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The first stage in image analysis, which seeks to simplify the data into its basic component elements or objects within the scene. Learn more in: Medical Hybrid Learning Tools

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Segmentation is the process of portioning a remote sensing mage into non-overlapping regions or segments. Learn more in: Application of Conventional UAVs for the Identification and Classification of Dense Green Spaces

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Process of partitioning a digital image into a disjoint set of connected pixels (known as regions). Learn more in: Image Analysis and Understanding Based on Information Theoretical Region Merging Approaches for Segmentation and Cooperative Fusion