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Tire -prints image enhancement method

Author: QiaoLi
Tutor: AiLingMei
School: Shaanxi Normal University
Course: Applied Computer Technology
Keywords: Tire prints Multiscale Retinex algorithm Wavelet decomposition and reconstruction Mallat fast wavelet decomposition
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 43
Quote: 0
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Abstract


With the number of car use in China has increased every year, steam first glance, traffic accidents and car hit and run case also will be increasing wheel imprint has become one of the most commonly used means of analysis in the handling of these cases and cracked. With the development of computer science, in particular the use of the tire-prints images collected by digital image processing technology to the scene of the accident for processing has become a road traffic accident liability analysis and identification of the vehicle as well as the analysis of the cause of the accident, but also to achieve the objective of dealing with traffic accidents , fair, fast and effective methods of science, but also for the development of a fast, convenient traffic processing software to provide new solutions. Tire-prints image enhancement processing pretreatment technology to further the image of the vehicle tire prints feature extraction and recognition. Tire-prints images extracted from the scene of the accident by the impact of the external environment, such as weather conditions, lighting, road conditions and other factors, so the majority of images collected from the scene showed the characteristics of low contrast and uneven illumination, noise, resulting in the individual characteristics of the tire tread image is blurred, the visual effect of the image with the actual needs, there is a great distance, for further follow-up image processing is extremely unfavorable, the tire-prints image enhancement is very necessary. But the vast majority of current tire prints image enhancement method is only a simple linear transformation of the image, gray stretch, the denoising traditional enhancement method, often resulting in the color of the image distortion, edge blur, detail loss, and enhance the effect is not very satisfactory, Based on this, we propose a highly specialized tire-prints image enhancement method through experimentation and simulation, can achieve better enhance reconnaissance vehicle was the case with a strong theoretical significance and application value. This paper first introduces the research background and significance of the vehicle tire marks, and described some of its research status and current research methods. And simply introduce the tire prints some of the basics of handling and tire marks were reviewed, the main work of this study are as follows: (1) for site acquisition tire-prints images exist uneven light intensity distribution, the background and objectives of low contrast the proposed enhancement algorithm based on the center surround Retinex theory, that the single-scale Retinex and multi-scale Retinex. Enhancement of the image is achieved by adjusting the dynamic range of the image, color constancy, image sharpening, in addition, in-depth study of the the Retinex theory calculation model and pointed out that the single-scale Retinex algorithm for image enhancement of the tire marks on the limitations, and through test to prove the superiority of the multiscale Retinex algorithm the tire imprint enhanced aspects. (2) there is a lot of noise and light sources are unevenly distributed in the tire-prints images in the proposed enhancement method based on wavelet decomposition and reconstruction of the image. First Mallat fast wavelet decomposition algorithm, tire prints image is decomposed into high-frequency and low-frequency components of different scales, and then the different components were de-noising, adjust brightness processing, to overcome the traditional method or only remove the image noise, or can only adjust the image's brightness distribution limitations.

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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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