以梯度臨界值控制函式分水嶺演算法為基礎之彩色影像分割

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题名:	以梯度臨界值控制函式分水嶺演算法為基礎之彩色影像分割
作者:	陳俊榮孫振東莊書瑋
贡献者:	資科系
关键词:	梯度臨界值彩色影像分割分水嶺 Gradient threshold Color image segmentation Watershed
日期:	2005-06
上传时间:	2010-06-01 10:16:34 (UTC+8)
摘要:	彩色影像分割是一項快速發展的數位影像處理技術，影像分割目的是將影像切割為數個不相重疊而各具有相同特性的區域或物件，典型的應用有物件抽取、物件辨識、以物件為基礎的影像壓縮、以及以內容為基礎的影像擷取等，近來有許多影像分割的相關技術與演算法被提出，其中分水嶺轉換(Watershed transformation)能有效地用在灰階與彩色影像分割，然而傳統的分水嶺轉換可能會產生嚴重的過度分割，也就是因原影像有許多局部最小點(Local minima)經轉換後產生許多小區域，本論文提出一個在梯度影像(Gradient image)裡去除無相關最小點(Irrelevant minima)的演算法，我們用梯度臨界值控制分割函式(Gradient-threshold-controlled segmentation function)之分水嶺轉換，全域梯度臨界值是由區域函式對臨界值的一次導數而得，根據實驗結果顯示本演算法對具不同特徵的影像，諸如是否有非均勻亮度、紋理、輪廓、與陰影等，皆可有效地改進分割精確性。 Color image segmentation is a rapidly developing technique of digital image processing. The goal of image segmentation is to divide the image into non-overlapping homogeneous regions or objects. Object extraction, object recognition, object-based compression, and content-based image retrieval are typical applications. Recently, a large number of techniques and algorithms have been proposed for image segmentation. Among them, those based on watershed transformation can be effectively used for segmentation of grey-scale and color images. However, conventional watershed transform may produce a severe over-segmentation of the image, i.e., many small regions are produced due to many local minima in the input image. In this paper we propose an algorithm for eliminating irrelevant minima in the resulting gradient images. We use gradient-threshold-controlled segmentation function for watershed transformation. The global gradient threshold is obtained from the first derivative of the region-function with respect to threshold. The experimental results show that the proposed algorithm can effectively improve segmentation accuracy for different image natures, such as presence or not of non-homogeneous illumination, texture, contours, and shadows.
關聯:	華岡工程學報 19期 P.51-63
显示于类别:	[工學院] 學報-華岡工程學報

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