Edge Affine Invariant Moment for Texture Image Feature Extraction
| Autor: | Jun Wang, Jun Qiang, Ganyi Tang, Yiwen Dou |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Image moment
Harris affine region detector business.industry Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Affine shape adaptation Computer Science::Graphics Image texture Feature (computer vision) Computer Science::Computer Vision and Pattern Recognition Hessian affine region detector Artificial intelligence Affine transformation business |
| Zdroj: | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783319607528 |
| DOI: | 10.1007/978-3-319-60753-5_9 |
| Popis: | Texture image feature extraction is one of hot topics of texture image recognition in recent years. As to this, a novel technique for texture image feature extraction based on edge affine invariant moment is presented in this paper. Firstly, each texture image is checked by a short step affine transformation Sobel algorithm initially. Then, the corresponding texture image feature named edge affine invariant moment will be calculated and added to feature vector set. Subsequently, cluster analysis will be loaded upon the set by K-means algorithm and the categorized texture image can be obtained. Three simulation experiments closed to real environment over the two well-known Brodatz and KTH-TIPS texture databases are performed in order to test the efficiency of our proposed algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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