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The Vehicle Image Retrieval Based on Multiple Vocabularies Index

Author: LiHui
Tutor: YangChenZuo
School: Xiamen University
Course: Computer technology
Keywords: Image Retrieval Vehicle Area Extraction Multiple Vocabularies Index
CLC: TP391.41
Type: Master's thesis
Year: 2014
Downloads: 3
Quote: 0
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Abstract


The vehicle image retrieval is an important part of intelligent transportation system. Vehicle retrieval has good application prospect in intelligent parking lot management, highway automatic charge, road monitoring and parking timeout detection. This paper comes from vehicle intelligent monitoring projects of highway service area, the problem bases on fixed background of vehicle image retrieval.Vehicle image retrieval has many relate technologies, such as vehicle detection, object area segmentation, feature extraction and feature matching, current technology in image retrieval is relatively mature. The purpose of this paper is to further study vehicle image feature fusion at indexing level, in response to the changes of illumination and luminance and to be able to make retrieval real-time. This article main research contents are as follows:1. Researching on the process and classical algorithm of image retrieval, analyze and summarize the key elements in the image retrieval process and feature extraction. Studying the advantages and disadvantages of different retrieval process and feature extraction methods, and analyze their feasibility in real-time vehicle image retrieval.2. Deformable part model based vehicle area segmentation. In order to reduce the retrieval time and workload of computional, first we need to carry on the vehicle localization, we extract feature only in vehicle regions, this greatly reduces the processing time, improving the efficiency of retrieval.3. The vehicle image retrieval based on multi-visual word index. We present a multi-dimensional index method to perform feature fusions of local symmetry feature and local color feature at indexing level. Specifically, two complementary features are coupled into a multi-dimensional inverted index. First we choose local symmetry feature to represent the vehicle image, it has strong illumination adaptability and invariance. To further enhance discriminative power of the visual word, we add local color feature to reflect distribution of local color in vehicle image. Thus, they form a complementary relationship with each other. We use bag of words as the retrieval model with TF-IDF weight, different feature descriptor is assigned to different weight.Through experimental analysis, vehicle image retrieval technique basing on multiple vocabularies index achieves good effect in accurate vehicle image retrieval.

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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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