Approaches for image segmentation applied to food. (2017)

• Record Type: Journal Article
• Authors: Martins, Pedro; Cruz, Igor; CecÁ¬lio, JosÁ¨; Abbasi, Maryam; Furtado, Pedro
• Is Part Of: International journal of applied pattern recognition. Volume 4:Number 2(2017)
• Page Start: 161
• Page End: 180
• Publication Date: 2017
• Subjects: image segmentation -- image clustering -- algorithms; Pattern perception -- Periodicals; Pattern recognition systems -- Periodicals; 006.405
• Languages: English
• ISSNs: 2049-887X

Abstract

For the task of image recognition, it is unpractical to process an image as a whole, since it is highly inefficient and most of the times challenging for the users. Image segmentation techniques are used to divide one image into multiple regions or clusters, it consists in assigning regions to each of the image pixels using different metrics such as pixel colour value, gray-scale intensity, edge finding algorithms, among others. The most diverse image segmentation algorithms have already been proposed and are currently used. However, there are three main categories of segmentation to which the existing algorithms can be assigned and we are going to discuss in this survey: region-based segmentation, data clustering, and edge-based segmentation. With this document, we study diverse commonly used segmentation algorithms, analyse their behaviour as well as their benefits and disadvantages, and present comparative experimental results when applied to a test image.