Abnormal Appearance Detection of Substation Based on Image Comparison

• Main Authors: Zhang Xu, Li Li, Li Jianxiang, Lyu Juntao, Huang Rui, Xing Haiwen
• Format: Article
• Language: English
• Published: EDP Sciences 2016-01-01
• Series: MATEC Web of Conferences
• Online Access: http://dx.doi.org/10.1051/matecconf/20165908001

Based on image comparison, a novel algorithm for abnormal appearance detection of substation is proposed. Previous spatial states of an object are compared to its current representation in a digital image. Firstly, saliency maps are acquired using a fast implementation method of salient region detection. Based on saliency maps, image registration was completed by ORB (Oriented Fast and Rotated Brief). Then, sliding widow algorithm is applied to transform the whole image comparison problem into sub-image comparison problem. Textural feature and shape feature vectors (TSFVs) representing contents of images are generated by feature level fusion. Finally, decisions are automatically made as to whether or not change at the outline has occurred by the Euclidean distance of TEFVs. Experimental results show that the proposed method has good performance in abnormal appearance detection of substation.