In this paper, a new class of image texture operators is proposed. We firstly determine that the number of gray levels in each B × B subblock is a fundamental property of the local image texture. Thus, an occurre...In this paper, a new class of image texture operators is proposed. We firstly determine that the number of gray levels in each B × B subblock is a fundamental property of the local image texture. Thus, an occurrence histogram for each B × B sub-block can be utilized to describe the texture of the image. Moreover, using a new multi-bit plane strategy, i.e., representing the image texture with the occurrence histogram of the first one or more significant bit-planes of the input image, more powerful operators for describing the image texture can be obtained. The proposed approach is invariant to gray scale variations since the operators are, by definition,invariant under any monotonic transformation of the gray scale, and robust to rotation. They can also be used as supplementary operators to local binary patterns(LBP) to improve their capability to resist illuminance variation, surface transformations, etc.展开更多
基金partially supported by the National Natural Science Foundation of China (61173147, 61332012, and U1135001)the National Basic Research Program of China (2011CB302204)+2 种基金the Fundamental Research Funds for Central Universities (12lgpy31)the Korea Foundation for Advanced Studies’ International Scholar Exchange Fellowship for the academic year of 2013–2014the MKE (The Ministry of Knowledge Economy), R. O. Korea, under the ITRC support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2010-C1090-1001-0004)
文摘In this paper, a new class of image texture operators is proposed. We firstly determine that the number of gray levels in each B × B subblock is a fundamental property of the local image texture. Thus, an occurrence histogram for each B × B sub-block can be utilized to describe the texture of the image. Moreover, using a new multi-bit plane strategy, i.e., representing the image texture with the occurrence histogram of the first one or more significant bit-planes of the input image, more powerful operators for describing the image texture can be obtained. The proposed approach is invariant to gray scale variations since the operators are, by definition,invariant under any monotonic transformation of the gray scale, and robust to rotation. They can also be used as supplementary operators to local binary patterns(LBP) to improve their capability to resist illuminance variation, surface transformations, etc.
