Abstract

This paper develops a new method for cluster segmentation of color texture image. At first, a color texture image has been decomposed three sub-bands that R (red), G (green), B (blue) channel. Second, each sub-bands channel has been decomposed by discrete wavelet transform (DWT) to the same resolution. Third, fusion operation is performed on the transformed images according to PCA- based (Principal Component Analysis) weighted average rule to choose the reconstructed coefficients. Then all the decomposed sub-bands images are reconstructed using inverse discrete wavelet transform (IDWT) that becoming a fusion image. Finally, k-means cluster segmentation algorithm has been applied for this fusion image, the segmentation results has been obtained. A number of experiments are performed to demonstrate the efficacy of the proposed method.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.