{"title":"基于LBP和订单池的特征描述","authors":"Lingda Wu, Wei Huang, Yingmei Wei","doi":"10.1109/ICVRV.2013.40","DOIUrl":null,"url":null,"abstract":"A novel local image descriptor named OCLBP(Order based Complete Local Binary Patterns) is proposed in this paper. It firstly extracts CLBP(Complete Local Binary Patterns) features pixel-by-pixel in the local image patch, and then pooled the CLBP features based on order relations of the pixel brightness in the patch. Specifically, the CLBP feature is based on CSLBP and adds the information of center pixel. The pattern number of the pixels is reduced compared to CSLBP. Furthermore, in order to better meet the scale invariance, the descriptors is extracted in multi-scales and the final descriptor is constructed by concatenating the histograms in multi-scales. The performance of the proposed descriptor is similar to the state-of-the-art descriptors SIFT and CSLBP in the condition of perspective transformation and light changes. In the condition of scaling, rotation, blurring, and JPEG compression, our descriptor has a better performance against the above descriptors using standard benchmarks.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Feature Description Based on LBP and Order Pooling\",\"authors\":\"Lingda Wu, Wei Huang, Yingmei Wei\",\"doi\":\"10.1109/ICVRV.2013.40\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel local image descriptor named OCLBP(Order based Complete Local Binary Patterns) is proposed in this paper. It firstly extracts CLBP(Complete Local Binary Patterns) features pixel-by-pixel in the local image patch, and then pooled the CLBP features based on order relations of the pixel brightness in the patch. Specifically, the CLBP feature is based on CSLBP and adds the information of center pixel. The pattern number of the pixels is reduced compared to CSLBP. Furthermore, in order to better meet the scale invariance, the descriptors is extracted in multi-scales and the final descriptor is constructed by concatenating the histograms in multi-scales. The performance of the proposed descriptor is similar to the state-of-the-art descriptors SIFT and CSLBP in the condition of perspective transformation and light changes. In the condition of scaling, rotation, blurring, and JPEG compression, our descriptor has a better performance against the above descriptors using standard benchmarks.\",\"PeriodicalId\":179465,\"journal\":{\"name\":\"2013 International Conference on Virtual Reality and Visualization\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Virtual Reality and Visualization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVRV.2013.40\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Virtual Reality and Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRV.2013.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
提出了一种新的局部图像描述符OCLBP(Order based Complete local Binary Patterns)。首先在局部图像patch中逐像素提取CLBP(Complete Local Binary Patterns)特征,然后根据patch中像素亮度的顺序关系对CLBP特征进行池化。具体来说,CLBP特征是在CSLBP的基础上增加中心像素的信息。与CSLBP相比,减少了像素的模式数。此外,为了更好地满足尺度不变性,在多尺度上提取描述子,并通过多尺度直方图的串联构造最终描述子。该描述子在透视变换和光变化条件下的性能与目前最先进的描述子SIFT和CSLBP相似。在缩放、旋转、模糊和JPEG压缩的条件下,我们的描述符与使用标准基准测试的上述描述符相比具有更好的性能。
Feature Description Based on LBP and Order Pooling
A novel local image descriptor named OCLBP(Order based Complete Local Binary Patterns) is proposed in this paper. It firstly extracts CLBP(Complete Local Binary Patterns) features pixel-by-pixel in the local image patch, and then pooled the CLBP features based on order relations of the pixel brightness in the patch. Specifically, the CLBP feature is based on CSLBP and adds the information of center pixel. The pattern number of the pixels is reduced compared to CSLBP. Furthermore, in order to better meet the scale invariance, the descriptors is extracted in multi-scales and the final descriptor is constructed by concatenating the histograms in multi-scales. The performance of the proposed descriptor is similar to the state-of-the-art descriptors SIFT and CSLBP in the condition of perspective transformation and light changes. In the condition of scaling, rotation, blurring, and JPEG compression, our descriptor has a better performance against the above descriptors using standard benchmarks.