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The Application of Reinforcement Learning and Relevance Feedback in Orthodontics Image Retrieval

Author: ZongLuYan
Tutor: WuChen
School: Jiangsu University of Science and Technology
Course: Applied Computer Technology
Keywords: Reinforcement Learning Relevance feedback Image Retrieval Orthodontics
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 12
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Abstract


With multimedia, the rapid development of network technology , there has been a large number of image information , the traditional text - based image retrieval method has been unable to meet the requirements of image information retrieval , and thus the content-based image retrieval (CBIR) has gradually become the current research focus . In order to better improve the retrieval efficiency , relevance feedback techniques introduced in image retrieval , a good human-computer interaction . Orthodontics image retrieval is an important part of the medical field of Orthodontics , efficient retrieval favor of to develop orthodontic program more quickly and accurately , improve the success rate . Characterization and image feature extraction CBIR core . This article describes the main features of color, texture and shape of the three kinds of extraction and image matching technology , which details the three colors of the image color space conversion formula , the extraction of various features highlights several major method. Next, given the evaluation criteria of image matching and image retrieval system . In subsequent tests , the selection according to the characteristics of the image of the orthodontic integrated feature retrieval method based on color and shape . Color feature extraction is based on the HSV space color histogram , Hu invariant moments of choice in terms of shape feature extraction . The results show that the comprehensive feature - based retrieval methods to overcome the lack of a single feature retrieval method , more comprehensively and effectively retrieve the image . Introduction of relevance feedback in image retrieval system can improve the retrieval performance . In this paper, on the basis of detailed feedback and reinforcement learning theory , reinforcement learning theory is introduced into the relevance feedback , relevance feedback method gives a combination of Q- learning with Bayesian theory and Orthodontics pictures library in Matlab7.0.1 the experiment, the effectiveness of the algorithm can be seen from the experiment . Finally , the article describes a simple relevance feedback image retrieval system using Matlab GUI .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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