基于优化采样模式的紧凑而快速的二进制描述子  

A Binary Descriptor Based on Both Optimized Sampling Pattern and Image Sub-patches

作　　者：惠国保[1] 李东波[1] 童一飞[1] 

机构地区：[1]南京理工大学机械工程学院,南京210094

出　　处：《自动化学报》2014年第2期255-266,共12页Acta Automatica Sinica

基　　金：国家自然科学基金(61104171)资助~~

摘　　要：进一步挖掘图像补丁特征信息,提出了一种鲁棒性更高的二进制描述子.针对传统的二进制描述子对旋转和视角变化鲁棒性差的问题,本文通过优化采样模式和分解图像补丁对其改进.首先,通过对最新提出的采样模式特点的分析、测试,发现采样点密度和平滑重叠度对产生的描述子独特性有重要影响;据此,调整这两个影响因子,设计出一种优化的采样模式.其次,利用像素点灰度值排序方法分解图像补丁,产生多个对应不同灰度段的亚补丁.最后,将优化的采样模式映射到亚补丁上,随机提取样本点进行灰度值比较测试.所得到的二进制描述子不仅包含了补丁像素的灰度比较信息,而且包含了灰度排序信息.通过对比实验看到本文的二进制描述子对特征识别匹配效果最好.本文的特征描述方法可应用于实时性要求高、内存紧凑的高质量目标识别.This paper proposes a more robust binary descriptor through further excavating feature information of image patch. Conventional binary descriptors such as binary robust independent elementary features （BRIEF） are not robust to rotation and viewpoint invariance, which is improved from two aspects in this paper. Firstly, an optimized sampling pattern is presented by tuning the density of sampling points and the overlapping size of receptive fields. Secondly, all pixels in the patch are classified according to their intensity order, so that the patch is decomposed into several sub- patches. Then, random tests on each sub-patch mapped with the optimized sampling pattern are repeatedly taken, and each test result is concatenated to form a distinct binary string of the sub-patch. The proposed descriptor encodes not only intensity-comparison information but also information about relative relationship of intensities. As a result, results based on experiments of performance evaluation have shown that the proposed binary descriptor outperforms the-state-of-the-art binary descriptors.

关 键 词：关键点 图像补丁 二进制描述子 采样模式 灰度排序 亚补丁 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]