A short-term learning approach based on similarity refinement in content-based image retrieval

Asma Shamsi; Hossein Nezamabadi-pour; Saeid Saryazdi

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A short-term learning approach based on similarity refinement in content-based image retrieval

机译：基于内容的图像检索中基于相似度细化的短期学习方法

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摘要

This paper presents a new relevance feedback approach based on similarity refinement. In the proposed approach weight correction of feature's components is done by a proposed rule set using mean and standard deviation of feature vectors of relevant (positive) and irrelevant (negative) images. Also, the weight of each type of features is adjusted according to the relevant images' rank in the retrieval based on only the same type of feature. To evaluate the performance of the proposed method, a set of comparative experiments on a general database containing 20,000 images of various semantic groups are performed. The results confirm the effectiveness of the proposed method comparing with two well-known methods.

机译：本文提出了一种基于相似度细化的新的相关性反馈方法。在提出的方法中，通过使用相关（正）图像和不相关（负）图像的特征向量的均值和标准偏差，通过提议的规则集完成特征成分的权重校正。而且，每种类型的特征的权重仅根据相同类型的特征根据检索中相关图像的等级来调整。为了评估该方法的性能，在包含20,000个不同语义组图像的通用数据库上进行了一组比较实验。结果证实了与两种众所周知的方法相比，该方法的有效性。

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来源
《Multimedia Tools and Applications》 |2014年第2期|2025-2039|共15页
作者
Asma Shamsi; Hossein Nezamabadi-pour; Saeid Saryazdi;
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作者单位

Department of Electrical Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169-133, Kerman, Iran;

Department of Electrical Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169-133, Kerman, Iran;

Department of Electrical Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169-133, Kerman, Iran;

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正文语种 eng
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关键词
Content-based image retrieval; Relevance feedback; Short-term learning; Similarity refinement; Query refinement;

机译：基于内容的图像检索;相关性反馈;短期学习;相似度细化;查询细化;

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专利

1. A Cluster-Based Approach for Efficient Content-Based Image Retrieval Using a Similarity-Preserving Space Transformation Method [J] . Biren Shah, Vijay Raghavan, Praveen Dhatric, Journal of the American Society for Information Science and Technology . 2006,第12期

机译：基于聚类的保留相似性空间变换方法的高效基于内容的图像检索方法
2. A novel similarity learning method via relative comparison for content-based medical image retrieval [J] . HuangW., ZhangP., WanM. Journal of digital imaging: the official journal of the Society for Computer Applications in Radiology . 2013,第5期

机译：基于内容比较的基于相对比较的新型相似度学习方法
3. A Novel Similarity Learning Method via Relative Comparison for Content-Based Medical Image Retrieval [J] . Wei Huang, Peng Zhang, Min Wan Journal of Digital Imaging . 2013,第5期

机译：基于相对比较的基于内容的医学图像检索新相似度学习方法
4. A new analysis framework for relevance feedback-driven similarity measure refinement in content-based image retrieval [C] . Jones, B.C., Wilkes, . 2001

机译：基于内容的图像检索中相关性反馈驱动的相似性度量细化的新分析框架
5. Content-based image retrieval by similarity learning for digital mammography. [D] . El Naqa, Issam M. 2002

机译：通过基于相似性学习的数字乳房X线照片基于内容的图像检索。
6. A Novel Similarity Learning Method via Relative Comparison for Content-Based Medical Image Retrieval [O] . Wei Huang, Peng Zhang, Min Wan 2013

机译：基于相对比较的基于内容的医学图像检索新相似度学习方法
7. A SHORT-TERM AND LONG-TERM LEARNING APPROACH FOR CONTENT-BASED IMAGE RETRIEVAL [O] . Michael Wacht, Juan Shan, Xiaojun Qi 2008

机译：基于内容的图像检索的短期和长期学习方法
8. Progressive content-based retrieval of image and video with adaptive and iterative refinement [R] . 1998

机译：基于内容的渐进式图像和视频检索，具有自适应和迭代细化

A short-term learning approach based on similarity refinement in content-based image retrieval

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