Approaches for image segmentation applied to food Online publication date: Fri, 21-Jul-2017
by Pedro Martins; Igor Cruz; Josè Cecìlio; Maryam Abbasi; Pedro Furtado
International Journal of Applied Pattern Recognition (IJAPR), Vol. 4, No. 2, 2017
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.
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