ABSTRACT
This chapter reviews image analysis as a tool for evaluation of food quality. Illumination is an important prerequisite of image acquisition for food quality evaluation. Acquisition of high quality image would naturally help to reduce the time and complexity of subsequent image processing steps, translating to a decreased cost of the image processing system and the quality of captured image is greatly affected by the lighting condition. Partitioning of an image into its constituent objects is known as Image segmentation which is a challenging task because of the richness of visual information in the image. The techniques of image segmentation developed for food quality evaluation can be divided into four different theoretical approaches, for example, thresholding-based, region-based, gradientbased, and classification-based segmentation. Thresholding-based segmentation is a particularly effective technique for images containing solid objects and having contrasting background, which distinguishes the object from the remaining part of an image with an optimal value.
