影像切割目的在於將影像切割為數個具有相同特性或是可視為一體的區域或物件，以此可以作為物件辨識、影像擷取的基礎，也可以為特定的壓縮方式增進其效能。本論文所題提出的方式是以分水嶺演算法為基礎。由於色彩間的差距不易定義，使得傳統分水嶺演算法不適合直接處裡彩色影像。本論文挑選合適的色彩空間，並根據其色彩模型，定義色彩對比梯度，再結合原影像之強度梯度，使其適用於分水嶺演算法。實驗結果顯示，本演算法可以有效避免過度切割的問題，並提供與人類視覺效果接近的分割結果。

　　The goal of image segmentation is to partition the image into several homogenous regions or particular objects with similar properties, such like color and texture. It is essential for object recognition and image retrieval, and it also could enhance the performance of certain compression algorithms. This thesis presents a watershed-based segmentation algorithm for color images. The conventional watershed segmentation algorithm is not suitable for color image directly, since it is hard to decide a suitable color gradient measurement for color image. The proposed algorithm choose a proper color model, definition of color contrast gradient and morphological intensity gradient for the improvement of watershed algorithm. Experimental result shows that the proposed algorithm can avoid the over segmentation problem, and produce segmented result which is close to human perception.

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