摘要
针对基于内容图像检索应用背景下局部二值模式(LBP)描述符缺乏空间描述能力及所需特征矢量维数较长的不足,提出一种基于LBP值对空间统计特征构建的改进纹理描述符(ILBP).ILBP描述符首先利用LBP微模式编码方法将原始图像转换为LBP伪灰度图像,然后再提取出多个关于LBP值对空间分布关系统计值构成描述图像特征的特征矢量.在基于内容的图像检索原型测试平台上完成大量实验.实验结果表明,与LBP及其各类变种描述符相比,ILBP描述符在进一步增强LBP描述符描述能力的同时大幅度压缩特征矢量维数,具有更好的查询正确率和查询效率.
The local binary pattern（LBP） descriptors employed in the content-based image retrieval system lack the abilities to describe the spatial relationships and have longer dimension of feature vector. In this paper, an improved LBP （ILBP） texture descriptor based on spatial statistical feature of LBP code pair is proposed. The original image is converted to the LBP pseudo image using LBP coding method for micro-pattern, and then several statistics of LBP code pair are extracted to form the feature vector for describing the texture attributes of images. Experiments are preformed on the content-based image retrieval prototype platform. Experimental results show that compared with other LBP descriptors the ILBP descriptor further enhances the description ability of LBP descriptor and substantially reduces the featurevector dimension with better query accuracy and query efficiency.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2013年第8期769-776,共8页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金项目(No.61163023)
国家863计划项目(No.2013AA013804)
江西省自然科学基金项目(No.20114BAB211024)
江西省省级教改项目(No.JXJG12124)资助
