Image segmentation and defect detection techniques using homogeneity

This paper presents a survey on latest image segmentation techniques using homogeneity. Homogeneity is one of the most widely used approaches for image segmentation because of its robust characteristics for texture segmentation. The existing image segmentation approaches suffer from the problem of over segmentation and leave a scope for enhancing accuracy of segmentation. To address the drawbacks of conventional image segmentation approaches homogeneity based approaches can be used which deal with image texture and thus provide better segmentation results.

This paper focuses on local homogeneity based approaches for image segmentation and image defect detection. For this the approaches like image local homogeneity analysis with region merging, local homogeneity analysis with discrete cosine transform, local homogeneity analysis with wavelet transform, homogeneity with FFD method, homogeneity with color features, local homogeneity with Gabor filtering and homogeneity with watershed algorithm are used.

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