Ceramic image retrieval method based on HSH-SIFT fusion features

Yongkang Peng; Jinjing Ma; Wenfang Cheng; Yu Nie

doi:10.1117/12.2601092

30 June 2021 Ceramic image retrieval method based on HSH-SIFT fusion features

Yongkang Peng, Jinjing Ma, Wenfang Cheng, Yu Nie

Proceedings Volume 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021); 118780C (2021) https://doi.org/10.1117/12.2601092
Event: Thirteenth International Conference on Digital Image Processing, 2021, Singapore, Singapore

Abstract

The SIFT (Scale Invariant Feature Transform) feature is a descriptor of the key points in the gray-gradient spatial. It cannot distinguish samples with the same SIFT features and the varied color distributions. The paper proposes a novel feature expression, named HSH-SIFT, which firstly extracts the SIFT feature of Value channel in HSV image, secondly calculates the hue-saturation histogram (abbrev. HSH) of the neighborhood of the key point and flatten it to be a 96-D vector, finally attaches the HSH vector to the tail of the corresponding SIFT feature vector to construct a 224-D fusion feature vector. Secondly, it proposes a fusion match strategy to improve the precision of content-based image retrieval, it fuses k-D tree, NNDR strategy, unified perspective transformation, and symmetric test to filter mismatched feature points. Experiments have shown that it significantly effects the precision of ceramic image retrieval and has been applied to ceramic image retrieval application.

Citation Download Citation

Yongkang Peng, Jinjing Ma, Wenfang Cheng, and Yu Nie "Ceramic image retrieval method based on HSH-SIFT fusion features", Proc. SPIE 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021), 118780C (30 June 2021); https://doi.org/10.1117/12.2601092

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