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Multi-feature -based image retrieval technology research and implementation

Author: ZhaoLiuQing
Tutor: HouALin
School: Changchun University of
Course: Signal and Information Processing
Keywords: Content-based Image Retrieval Clothing image Feature Extraction Similarity measure Background Removal
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 89
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Abstract


With the increasing development of online shopping system and perfect, this way of shopping is increasingly favored by consumers. In this system, consumers need to select the product drawing product, so a large demand for image retrieval arises. Online shopping areas, businesses for each commodity shoot a single image, the image that we are interested only in the area of ??clothing, for this feature, this paper based on edge detection image background removal technique used to reduce background on The extracted image features of interference; merchants for goods when taking pictures, it might be inclined clothes placed to achieve a better visual effect, it requires to be retrieved image features should have a rotation invariance. Characteristics of the image of clothing, clothing categories shape features of the image to identify, varieties of clothing with the color and texture characteristics to identify. Therefore, it is difficult to apply a single image features a comprehensive description of the characteristics of clothing image to image retrieval based on a single feature is difficult to meet the user's requirements, so the proposed combination of color, texture and shape of multi-feature image retrieval algorithm, as complete as possible describe the image in order to achieve better search results. In this paper, clothing image feature extraction, similarity measure as the main line, combined with the clothing image features, analysis and comparison of domestic and foreign content-based image retrieval algorithm focuses on the representation of the visual feature descriptor extraction and similarity measurement algorithm. Select the object of study in this paper, in order to take clothes tiled images. Given the characteristics of the image itself apparel, paper use Fourier descriptors and moment invariants describe the shape of the image feature, the choice is more close to human visual characteristics HSI color space is 72-dimensional color histogram quantized description of the image's color characteristics, with the with a rotation invariant LBP histograms describe the image texture features. In this retrieval algorithm, do first shape-based image retrieval, and then do the image segmentation algorithm background removal, and then characterized by the shape retrieved from an image based on color and texture features to make the search. Construct a multi-feature-based image retrieval apparel prototype system implemented based on the combination of clothing image color, texture and shape features automatic extraction, similarity matching, and secondary retrieval retrieval system, using VC 6.0 to achieve. The experiments demonstrate that the proposed background removal based image retrieval technology and multi-feature-based image retrieval effectiveness and feasibility. The characteristics of multi-feature combined with a single retrieval algorithm to compare the experimental results will be applied and unapplied background removal technique to compare the experimental results indicate that the same image library and similarity measure, the application of multi-feature combines search results more Well, while the background removal technology not only improves the retrieval speed, but also improves the quality of search, thus confirming that the proposed search algorithm for image retrieval clothing feasibility and effectiveness. In this thesis, research and practice for the promotion of multi-feature-based image retrieval algorithm development garment has a certain reference value.

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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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