Image Local Feature Descriptor Based on Discrete Cosine Transform
Jing Zhao · Jisuanji gongcheng · 2012
Because Scale Invariant Feature Transform(SIFT) descriptor is likely influenced by illumination changes,this paper proposes a kind of Discrete Cosine Transform(DCT)-based local invariant feature descriptor.The descriptor uses the characteristics of DCT,ignoring high-frequency coefficients,and reduces the dimension.It is composed of a small numbers of compositions of low-frequency coefficient matrix.As the sign of the DCT frequency coefficient is not sensitive to illumination changes,the proposed descriptor improves the descriptor distinction by setting penalty factor in the calculation of the distance between the descriptors.Result of the implementation test shows that the proposed descriptor has better significance,recall rate and precision than SIFT descriptor.