本篇論文的目的是為了改善影像受光的照度影響，並以CIELAB色彩空間做為描述影像的基礎，且設計一部利用影像辨識來追蹤特定目標物之自走車。在辨識目標過程中，分析RGB色彩空間與CIELAB色彩空間兩者受光的亮度影響。可以發現當使用CIELAB之影像可避免因受到亮度的影響所造成影像資料的判斷錯誤。並能將物體從動態背景中分離出來與計算物體移動之方向，根據移動方位的資訊透過運動控制器計算出力量大小，進而從藍芽傳輸傳回至車上的控制器中，控制自走車前進方向達到追蹤目的。實驗中將以加入類似目標的雜訊、動態中改變環境光源、面向點光源的辨識等實驗來說明。結果顯示，經由本論文所提出之方法，可避免受亮度影響並且得到正確影像資訊並追蹤目標。

This study aims to present a method of processing digital images by reducing the effect due to brightness. In this study, the images are described on the basis of CIELAB color space and the data are used to design an activated motorized car which can trace the target by means of phantom identification techniques. During the process of identifying the target, the influence of brightness on the RGB color space and the CIELAB color space are analyzed. Images using CIELAB are free from the disturbance of brightness which may cause errors of phantom identification. In addition, images using CIELAB can be separated from the background and the direction of the target’s movement can be computed. The data obtained can be transmitted to the controller of the car wirelessly and then direct the car to trace the target. Three different scenarios are tested, which are (1) adding the noise similar to the target; (2) changing the surrounding light sources in the movement; (3) identification of the point-light sources. By adopting the methods proposed in this study, the disturbance of brightness can be successfully avoided, the data of the correct image can be obtained, and the target can be tracked.

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