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| Recommending Image Based on Feature Matching |
Liu Dongsu, Huo Chenhui( ) |
| School of Economics and Management, Xidian University, Xi’an 710071, China |
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Abstract [Objective] This paper developed an image recommendation model based on feature matching technique and the LSH algorithm, aiming to improve the accuracy of recommendations. [Methods] First, we extracted the image’s SIFT features as the matching criteria. Then, we modified the LSH algorithm to retrieve images in high dimensional settings. Finally, we proposed an ICF-LSH algorithm based on the collaborative filtering techniques to build fusion recommendation model. [Results] We examined the proposed algorithm with various datasets and achieved better recall and precision rates for image recommendation. [Limitations] Only used the SIFT feature to extract image features. More research is needed to explore other matching features. [Conclusions] The proposed model improves the performance of image matching and recommendation systems.
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Received: 13 October 2017
Published: 03 April 2018
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