title: Multiscale distance coherence vector algorithm for content-based image retrieval.
abstract: Multiscale distance coherence vector algorithm for content-based image retrieval (CBIR) is proposed due to the same descriptor with different shapes and the shortcomings of antinoise performance of the distance coherence vector algorithm. By this algorithm, the image contour curve is evolved by Gaussian function first, and then the distance coherence vector is, respectively, extracted from the contour of the original image and evolved images. Multiscale distance coherence vector was obtained by reasonable weight distribution of the distance coherence vectors of evolved images contour. This algorithm not only is invariable to translation, rotation, and scaling transformation but also has good performance of antinoise. The experiment results show us that the algorithm has a higher recall rate and precision rate for the retrieval of images polluted by noise.
authors.affiliation: School of Software, Nanchang Hangkong University, Nanchang 330063, China.
authors.forename: Zeng
authors.initials: Z
authors.lastname: Jiexian
authors.affiliation: School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China.
authors.forename: Liu
authors.initials: L
authors.lastname: Xiupeng
authors.affiliation: School of Information Science and Engineering, Hunan University, Changsha 410082, China.
authors.forename: Fei
authors.identifier: 0000-0002-2217-578X
authors.initials: F
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D007090:Image Interpretation, Computer-Assisted; D016247:Information Storage and Retrieval / Q000379:methods*; D008962:Models, Theoretical; D012984:Software