Photometric invariant feature descriptor based on SIFT  

作　　者：高明亮 杨晓敏 余艳梅 罗代升 

机构地区：[1]College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China

出　　处：《Chinese Optics Letters》2012年第B06期63-68,共6页中国光学快报（英文版）

摘　　要：For many years, various local feature descriptors have been proposed. Among them, Lowe＇s scale invariant feature transform （SIFT） descriptor is the most successful one and has been proven to be performed better on the distinctiveness and robustness than other descriptors. However, SIFT descriptor is based on gray level images and pays little attention to the color information which can be a powerful cue in the distinction and recognition of objects. To increase the discriminative power, color features have been plugged into the feature descriptors only recently. In this letter, we study the photometric invariant properties of the Lowers SIFT, HueSIFT, rgSIFT and CSIFT based on color diagonal offset model. Theoretical and experimental results show that the four descriptors are not fully invariant to photometric transformation. To solve this problem, a new color invariant framework based on color diagonal offset model is proposed in this letter. Exnerimental results validate our Dronosed framework.For many years, various local feature descriptors have been proposed. Among them, Lowe＇s scale invariant feature transform （SIFT） descriptor is the most successful one and has been proven to be performed better on the distinctiveness and robustness than other descriptors. However, SIFT descriptor is based on gray level images and pays little attention to the color information which can be a powerful cue in the distinction and recognition of objects. To increase the discriminative power, color features have been plugged into the feature descriptors only recently. In this letter, we study the photometric invariant properties of the Lowers SIFT, HueSIFT, rgSIFT and CSIFT based on color diagonal offset model. Theoretical and experimental results show that the four descriptors are not fully invariant to photometric transformation. To solve this problem, a new color invariant framework based on color diagonal offset model is proposed in this letter. Exnerimental results validate our Dronosed framework.

关 键 词：SIFT 特征描述 光度 颜色特征 描述符 局部特征 特征变换 提示信息 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN912.3[自动化与计算机技术—计算机科学与技术]