A Novel Feature Descriptor Invariant to Complex Brightness Changes
Tang, Feng; Lim, Suk Hwan; Chang, Nelson L.
Keyword(s): brightness invariance, illumination invariant, feature descriptors, image features, feature matching, correspondences
Abstract: We describe a novel and robust feature descriptor called ordinal spatial intensity distribution (OSID) which is invariant to any monotonically increasing brightness changes. Many traditional features are invariant to intensity shift or affine brightness changes but cannot handle more complex nonlinear brightness changes, which often occur due to the nonlinear camera response, variations in capture device parameters, temporal changes in the illumination, and viewpoint-dependent illumination and shadowing. A configuration of spatial patch sub- divisions is defined, and the descriptor is obtained by computing a 2-D histogram in the intensity ordering and spatial sub-division spaces. Extensive experiments show that the proposed descriptor significantly outperforms many state-of-the-art descriptors such as SIFT, GLOH, and PCA-SIFT under complex brightness changes. Moreover, the experiments demonstrate the proposed descriptor's superior performance even in the presence of image blur, viewpoint changes, and JPEG compression. The proposed descriptor has far reaching implications for many applications in computer vision.
Additional Publication Information: To be published and presented at IEEE Conference on Computer Vision and Pattern Recognition, June 2009.
External Posting Date: April 6, 2009 [Fulltext]. Approved for External Publication
Internal Posting Date: April 6, 2009 [Fulltext]