STUDY ON INTERACTIVE METHODS FOR IMAGE SEGMENTATION

ELECTRONICS ENGINEERING

Segmentation partitions an image into distinct regions containing each pixels 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. Meaningful segmentation is the first step from low-level image processing transforming a grayscale or color image into one or more other images to high-level image description in terms of features, objects, and scenes. Interactive segmentation became popular because in different domains, user interaction is available, and it can greatly reduce the ambiguity of segmentation caused by complex object appearance, weak edges, etc. Global optimization, often formulated as a graph problem, became popular because it is more robust compared to the local methods such as thresholding or region-growing. These methods overcome the problems in old traditionally used approaches as they not only consider local pixel-based features, but also look at global similarities within the image. This paper reviews various interactive image segmentation methods and their algorithms.

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