Research on Infrared Image Segmentation of Power Equipment Using Niblack Optimized by Bat Algorithm
| Autor: | Huo Sijia, Guo Wencheng, Ma Hongwei, Hao-Yang Cui, Qin Lunming, Ge Chenhang |
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| Rok vydání: | 2018 |
| Předmět: |
Infrared image
Fitness function Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Image segmentation Otsu's method symbols.namesake symbols Segmentation Artificial intelligence Infrared image segmentation business Bat algorithm Power equipment |
| Zdroj: | DEStech Transactions on Engineering and Technology Research. |
| ISSN: | 2475-885X |
| DOI: | 10.12783/dtetr/pmsms2018/24925 |
| Popis: | Infrared image segmentation of power equipment is the basis for intelligent diagnosis of power equipment faults. In order to reduce the influence of non-uniform background on the infrared image segmentation of power equipment and improve the accuracy and efficiency of image segmentation, an improved Niblack image segmentation method based on bat algorithm is proposed. This method uses the variance between classes as the fitness function of the bat algorithm to automatically search for the optimal segmentation threshold of the non-overlapping rectangular neighborhood in the Niblack method, and uses it for binarization of the current neighborhood to extract target area from the infrared image. Experimental results show that compared with the traditional Otsu method, Niblack method and other algorithms, the segmentation algorithm reduces the ME by at least 34% to 84%. Compared with the BA+Otsu method, the average time consumption is reduced by 70%, effectively improving the accuracy and efficiency of the infrared image segmentation detection of the device. |
| Databáze: | OpenAIRE |
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