使用去反光機制作車輛顏色分類

Vehicle Color Classification Using the Specular-Free Mechanism

李端賢(Tuan-Hsien Lee)

指導教授 ： 李素瑛

國立交通大學/資訊學院/資訊科學與工程研究所/碩士(2011年)

https://doi.org/10.6842/NCTU.2011.00880

摘要

在自動化的車輛監視系統中，顏色辨識是一項重要的議題。車輛的顏色是一項重要的特徵，它可以幫助我們去辨識這輛車子的身分。在這篇論文中，我們提出一個以降低反光影響的方法去分類車輛的顏色。首先，使用影像切割演算法把影像切成幾個區域，找出最有可能是車輛外殼的那個區域。由於受到車殼上反光的影響，會使得影像切割後車殼會變成幾塊破碎的區域，我們將很難找到完整的車輛外殼的區域。因此，我們使用了一個去反光的方法分開反光的成分和漫射的成分，以降低反光所造成的影響。最後，我們找出車輛車殼的區域，計算它的主要顏色以分類車輛的顏色。我們從幾個不同的網站上下載七種不同顏色的車輛圖片當作實驗的資料，實驗的結果顯示出我們提出的方法有令人滿意的結果。

關鍵字

車輛顏色分類 ； 去除反光

並列摘要

Color recognition is an important issue in automatic vehicle surveillance. The vehicle color is a critical feature to help identify cars. In this thesis, we propose a novel approach for vehicle color classification. Firstly, we use image segmentation algorithm to divide image into regions and extract the vehicle shell part from them. Since the light reflection will influence, the broken regions on car shell after image segmentation, we can’t find a complete car shell well in images. Thus, we use the specular-to-diffuse mechanism to separate specular component and diffuse component and reduce the light reflection influence. Finally, we extract the vehicle shell region and calculate the dominant color of the shell region to classify the vehicle color. We download the 7 kinds of different color vehicle images from Internet web sites. The experimental results demonstrate good performance and thus show the effectiveness of the proposed schemes.

並列關鍵字

Vehicle Color Classification ； Light Reflection Removal

參考文獻

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