| Lin Lijun (林丽君)*,He Mingge**,Yin Ying*,Yin Xiangyun*,Yin Guofu*.[J].高技术通讯(英文),2015,21(3):276~281 |
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| Edge detection of magnetic tile cracks based on wavelet |
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| DOI：10.3772/j.issn.1006-6748.2015.03.005 |
| 中文关键词: |
| 英文关键词: edge detection, wavelet transform, textures processing, magnetic tile, information entropy |
| 基金项目: |
| Author Name | Affiliation | | Lin Lijun (林丽君)* | | | He Mingge** | | | Yin Ying* | | | Yin Xiangyun* | | | Yin Guofu* | |
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| 中文摘要: |
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| 英文摘要: |
| In order to extract the defect edge information on the magnetic tile surface with low contrast and textured background, an edge detection algorithm based on image weighted information entropy and wavelet modulus maxima is proposed. At first, a new Butterworth high pass filter (BHPF) with adaptive cutoff frequency is produced, because the clarity and complexity of the textured background are described by the weighted information entropy of the image gradient variance quantitatively, and the filter can change its parameters through matching the non-linear relationship between the information entropy and the cutoff frequency. And then, the best decomposition scale is obtained by the level determination function to prevent edge information from missing. At last, edge points are got by double threshold after obtaining the wavelet modulus maxima, and then the edge image is linked by the edge points to ensure the edge continuity and veracity. Experiment results indicate that the proposed algorithm outperforms the conventional Canny and Sobel algorithm, and the edge detection algorithm can also detect other defects, and lays the foundation for defecting auto- recognition. |
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