Texture Image Segmentation using Morphology in Wavelet Transforms

Authors

  • V Vijaya Kumar

  • V Vijaya Kumar

Keywords:

morphology, top hat transform, local contrast, otsu threshold

Abstract

One of the essential and crucial steps for image understanding, interpretation, analysis and recognition is the image segmentation. This paper advocates a new segme- ntation scheme using morphology on wavelet decomposed images. The present paper provides a good segmentation on natural images and textures by dividing an image into non overlapping regions, which are homogenous in terms of certain features such as texture, spatial coordinates etc. using simple morphological operations. Morphological enhancement technique based on Top Hat transforms enhances the local contrast in this paper. The morphological treatment and followed by Otsu2019;s threshold overcomes the problem of noise and thin gaps, and also smooth the final regions. The experimental results on four different databases demonstrate the success of the proposed method, compared to many other methods.

How to Cite

V Vijaya Kumar, & V Vijaya Kumar. (2017). Texture Image Segmentation using Morphology in Wavelet Transforms. Global Journal of Computer Science and Technology, 17(F1), 1–17. Retrieved from https://computerresearch.org/index.php/computer/article/view/1505

Texture Image Segmentation using Morphology in Wavelet Transforms

Published

2017-01-15