Image segmentation using fuzzy logic, neural networks and genetic algorithms: survey and trends
Machine Graphics & Vision International Journal
A parallel solution for high resolution histological image analysis
Computer Methods and Programs in Biomedicine
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Image segmentation has been the subject of considerable research activity over the last three decades. This paper proposes an algorithm for color image segmentation by region growing combined with the image enhancement based on the Bezier model. Using Bezier curve model has a direct impact on the quality of the image, and will enhance the boundary differences between the objects and their background making the image segmentation task easier. The segmentation starts from a seed in the form of 3*3 image blocks to avoid the noise point. It grows up the region by adding adjacent pixels that are satisfied with the homogeneous criteria with the seed point, expand point and the growing region respectively. Using the perceptual color clustering, color images is quantized and the similar colors are classified based on NBS color distance. The experimental results illuminate that the algorithm the paper proposed is effective.