應用電腦視覺技術的車牌辨識系統

A Vision-based Car License Plate Recognition System

吳宜軒(Yi-Hsuan Wu)

指導教授 ： 陳彥霖

亞洲大學/資訊學院/資訊工程學系碩士班/碩士(2009年)

摘要

本論文提出一套基於電腦視覺的車牌辨識系統，可區分為四大步驟，包括了影像前處理、車牌定位、字體切割及字元辨識。在影像前處理部份，將透過視訊鏡頭拍攝到的RGB影像轉成灰階影像，將灰階影像轉成二值化影像，並經過中值濾波濾除雜訊；在車牌定位部份，對二值化影像內可能的車牌位置進行預估，利用一般車牌的長與寬得到車牌的位置；在字體切割部份，利用車牌字元與背景之間高對比的特性，將車牌的字元切割出來；最後使用類神經網路做為辨識功能，將車牌上的文數字辨識出來。此外於本論文中我們額外利用Bottom-hat方法加強車牌影像特徵，對辨識度的提昇有明顯的效果。

關鍵字

車牌定位、字元切割、字元辨識、 Bottom–hat、Otsu ； HASH(0xa1621e0) ； HASH(0xa16221c)

並列摘要

This paper presents a license plate recognition system based on the computer vision, including five parts which are image pre-processing, license plate locating, character segmentation and recognition. In the image pre-processing part, the RGB images obtained from the camera are changed into the gray images. After the gray images are changed into the binaries images, and the noises are filtered by using the median filter. In the license plate locating part, we predict the possible location of the license plate in the binaries image and acquire it with using the length and width value of the general license plate. In the character segmentation part, the characters of the license plate are segmented due to the high contrast between those and the background. At last the neural network is adopted into the pattern recognition, and the letters and numbers could be recognized. Moreover, we exploit the Bottom-hat module to enhance the features of the license plate in order to promote the identification significantly.

並列關鍵字

license plate location, character segmentation, character reorganization, Bottom-hat, Otsu method.

參考文獻

灣師範大學資訊教育研究所， 2000。

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[1] N, Otsu., “A Threshold Selection Method from Gray-Level Histograms, ” IEEE Transactions on Systems , Man, and Cybernetics, Vol.9, No. 1, pp. 62-66, 1979.