Evaluation of wavelet-based salient point detectors for image retrieval
- 作者: Jian M.1,2
-
隶属关系:
- School of Computer Science and Technology
- Department of Computer Science and Technology
- 期: 卷 27, 编号 4 (2017)
- 页面: 723-730
- 栏目: Representation, Processing, Analysis, and Understanding of Images
- URL: https://bakhtiniada.ru/1054-6618/article/view/195232
- DOI: https://doi.org/10.1134/S1054661817040137
- ID: 195232
如何引用文章
详细
Content-based image retrieval system based on global visual content features normally return the retrieval results according to the similarity between features extracted from the sample query image and candidate images. However, global features usually cannot capture different characteristics of different parts in the image. Therefore, the representation of local image properties is one of the most active research issues in content-based image retrieval. The method based on salient point detection is one of the typical and effective approaches. This paper proposes three improved salient point detectors based on wavelet transform, which are calculated in the three different orientations’ and scales’ subbands and weighted equally. In contrast to the former method based on salient point detection, the improved salient point detectors aim to extract the visual information in the image more effectively. We have tested the proposed schemes and compared four salient point detectors using a wide range of image samples from the Corel Image Library, and experimental results show that the improved salient point detectors have produced promising results.
作者简介
Muwei Jian
School of Computer Science and Technology; Department of Computer Science and Technology
编辑信件的主要联系方式.
Email: jianmuweihk@163.com
中国, Jinan; 238 Songling Road, Qingdao
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