基于感知哈希和SURF的电力设备红外图像检索

Guohui Zhou, Lijun Xiao, Xingyu Pei, Chenxi Li, Huiping Qin, Jinpeng Zhang, Z. Fang
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引用次数: 4

摘要

本文提出了一种识别可见光图像库中与给定红外图像最相似图像的方法。首先对可见光和红外图像分别进行边缘提取的方法,然后采用感知哈希编码方法对边缘图像进行编码,并通过比较两种图像哈希编码的汉明距离得到图像相似度。由于红外图像噪声较多,基于像素值的感知哈希算法可能存在判断误差,因此利用哈希算法对3张可见光图像进行相似度比较,利用SURF算法对相似度进行比较。基于斜率一致性,得到两个图像匹配点。选取匹配点最明显的图像作为与红外图像最相似的图像。实验结果表明,该方法可以识别出红外图像与可见光图像库相似度最高的可见光图像。
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Paper infrared image retrieval of power equipment based on perceptual hash and SURF
This paper presents a method for identifying the most similar image in the visible image library and the given infrared image. First the method of visible and infrared image edge extraction respectively, and then use the perceptual hash encoding method of edge image, and get the image similarity by comparing the two image hash encoding Hamming distance. As the infrared image noise more perceptual hash algorithm based on pixel values may have errors of judgment, so the use of hash algorithm to get similarity on the 3 visible images using the SURF algorithm to compare the similarity. Based on the slope consistency, two image matching points are obtained. The most visible images of matching points are selected as the most similar images to infrared images. Experimental results show that the method can identify the visible image with the highest similarity between infrared image and visible image library.
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