在不同的光源環境下，顏色的資訊會隨著環境而改變，因此要做到穩定的膚色辨識並不容易。先前的研究指出，人類的膚色大致上可歸納於特定顏色座標系統中的一段範圍內。但是根據我們的實驗，這段範圍會隨著環境光源的改變而產生偏移，因此運用相同的標準，無法在不同的場景下做到準確的膚色辨識與切割。針對這個議題，我們提出利用影像中非色彩的資訊，找出最符合膚色的範圍。具體來說，借重臉部偵測獨立於色度的特性，我們使用臉部偵測的結果，做為調整膚色範圍的依據。實驗所得到的辨識結果，效能與效率都足以運用在以視覺為基礎的人機介面，例如手部與指尖偵測。 / Robust detection of skin color is a difficult task since color information changes under different lighting conditions. Previous research indicated that human skin color is restricted to a small range of values in certain color coordinate systems. However, the ranges tend to shift with varying illumination according to our experiments. It is therefore unattainable to derive a universal standard for skin color detection and segmentation for general scenes. To address this issue, we propose to use achromatic features to identify the proper ranges of skin color in an image. Specifically, we utilize the result of face detection, which is independent of chromatic properties, to guide the process of skin color range selection. Experimental results have validated the efficacy and efficiency of the proposed methodology for vision-based human-computer interface such as hand and finger detection.

This master’s thesis is dealing with recognition of an easy static gestures in order to computer controlling. First part of this work is attended to the theoretical review of methods used to hand segmentation from the image. Next methods for hang gesture classification are described. The second part of this work is devoted to choice of suitable method for hand segmentation based on skin color and movement. Methods for hand gesture classification are described in next part. Last part of this work is devoted to description of proposed system.