A new approach for texture segmentation based on NBP method
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- 作者：Izem Hamouchene ; Saliha Aouat
- 关键词：Texture analysis ; Features extraction ; Texture matching ; Decomposing architecture ; Pattern Recognition ; Texture segmentation
- 刊名：Multimedia Tools and Applications
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：76
- 期：2
- 页码：1921-1940
- 全文大小：
- 刊物类别：Computer Science
- 刊物主题：Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems;
- 出版者：Springer US
- ISSN：1573-7721
- 卷排序：76
文摘
Nowadays, image processing is an interesting research area due to the growth of the communication technologies. Matching problem, which consists of localizing one texture in an image, that contains several textures is one of the fundamental problem of image processing and pattern recognition. In this paper, a new feature extraction method and texture segmentation system are proposed. The proposed method (RINBP) is robust against rotation and improves the ability of extracting the local information. The segmentation architecture follows several steps. First, fixing a converging point α. After that, a Main analysis Window (MW) starting from α to the bottom left corner of the image is determined. Then, several possible windows are extracted and the feature extraction method is applied on each window. Finally, a similarity measure is calculated in order to decide if this window is pertinent or not. This process is stopped until the size of the MW reaches a minimum size. Each pertinent window increases the relevance of the desired texture in the output image. Finally, an image of relevance is obtained by considering the most relevant area. For the experiments, textured images generated from Brodatz album database are used. The experiments have shown the superiority of our method compared to other existing methods. The obtained results have illustrated the robustness and the efficiency of the proposed segmentation method based on the relevance of the analysis windows.