ROI Extraction Method of Infrared Thermal Image Based on GLCM Characteristic Imitate Gradient
| Autor: | Xiang-Gong Hong, Li Zhu, Hui Shen, Weike Chang |
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| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | Communications in Computer and Information Science ISBN: 9789811072987 CCCV (1) |
| DOI: | 10.1007/978-981-10-7299-4_16 |
| Popis: | Automatic inspection of UAV (unmanned aerial vehicle) vision in photovoltaic power station is of great significance in effectively capturing high-definition images and quickly detecting the fault area, which can reduce the risk of false detection and lower the cost of manual operation. However, due to the complexity of photovoltaic power station environment, disturbance often occurrence on images, leading up to the misjudgment of the fault area. We proposed a method to extraction region based on the gray level co-occurrence matrix (GLCM) and textural features. The image extraction from target area can be achieved by extracting feature images, gradient imitate and region filling. This method effectively combines the textural features of images with edge features of the gradient images. A comparison is made between the algorithm promoted in this paper and the grab cut method, on the basis of the labeled image segmentation algorithm. It turns out that the mean precision and mean recall of the proposed imitation gradient image extraction method are higher than that of the grab cut algorithm, and the Recallvalue, F index and J index are better than the grab cut algorithm. A new algorithm is proposed construct filling model by using gradient image and a morsel of texture feature calculated by GLCM method. The advantages of the proposed algorithm are fewer interactive tags, fewer manual labels. Therefore, the image detection of fault area can be better realized. |
| Databáze: | OpenAIRE |
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