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Integration of visual perception and psychological color model for image retrieval technology

Author: WuYuanRen
Tutor: ChenDuanSheng
School: Huaqiao University
Course: Computer technology
Keywords: Image Retrieval Chroma vector triangle Vector three color pyramid Feature Extraction VR space color histogram Grayscale conversion
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 37
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Abstract


Multimedia technology popularization and implementation of Internet technologies has led to the emergence of a large number of image information, the traditional text-based keyword search image information retrieval methods have been unable to meet the requirements, which makes content-based image retrieval technology has become the current research hotspot. This paper introduces the topic of meaning and context, content-based image retrieval technology research status do a simple analysis, and on this basis in the field discussed some key technologies involved. In the current practice, content-based image retrieval system design is often for a specific environment and the use of specific algorithms. The physical characteristics of the color image is characterized by the most direct visual characteristics, relative to other features, the color feature is relatively stable, the image translation, scaling, rotation and other changes are not sensitive, and highly robust. Therefore, in this paper the implementation of image retrieval system, mainly using the color-based image retrieval algorithms. In-depth study of the image based on color feature extraction, this paper describes the function of the degree of concern about the color based on the structure in the HSV color space chromaticity vector triangles, and extracting chrominance vector triangle inscribed circle of radius R as the corresponding color space the H, S-dimensional feature vector, and its third dimension, the value V be quantified characteristics, combined with the color information extraction combined spatial matrix VR, that space as the color histogram feature image retrieval, so that a three-dimensional color space will reduced to two-dimensional vector using Euclidean distance similarity measure through space with the traditional color histogram as the feature retrieval compared. Experiments show that the proposed VR HSV color space based spatial color histogram image retrieval method can efficiently retrieved from the image database target image. Subsequently, the paper continues to apply in the RGB color space, each pixel geometric knowledge of R, G, B color vector of the pixel values ??to construct a triangular pyramid model, and extracted three pyramid inradius as the pixel of the feature, which will original color image into a grayscale image, the color space is converted into a three-dimensional image information amount is reduced to one-third of the original, the color space information with the same gray-scale image to extract color histogram as a feature space, using Euclidean distance for image retrieval. Experiments show that the proposed three pyramid-based color vector images inradius gray and retrieval method can efficiently retrieved from the image database target image. Finally, content-based image retrieval technology research and implementation are summarized on the current content-based image retrieval technology difficulties faced were analyzed, and further research directions. The main innovation of this paper is to: (a) presents a VR space HSV color space color histogram feature extraction method. This method is to some extent considered reasonable correlation between the respective color components, the calculation of the vector space in a natural way converted into scalar calculations, in terms of ideology is a new algorithm is different from the other algorithms. Experimental results show that this method can effectively retrieve from the image database target image. (2) further applications of the knowledge of geometry presents a grayscale image conversion and retrieval methods. This approach will also calculate the vector space in a natural way converted into scalar calculations, experiments show that the method is reasonable and practicable.

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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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