Abstract

Morphological image processing has been widely used for segmentation of binary, grayscale and color images. To extend the concept of segmentation, an ordering of the data is required. In this research paper, an effective methodology for digital color image segmentation has been publicized with stochastic gradients and watershed algorithm. The results demonstrate that combining of these two strategies has been very helpful for image segmentation and for computer vision, even in noisy images. The efficiency of the proposed methodology has been explained by experimental results and statistical measurements.

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