文章基本信息

标题：Innovative Segmentation Approach based on LRTM
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作者：S.Kezia ; I.Shanti Prabha ; V.VijayaKumar 等
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2012
卷号：2
期号：5
页码：229-233
出版社：International Journal of Soft Computing & Engineering
摘要：Texture refers to the variation of gray level tones in a local neighbourhood. The “local” texture information for a given pixel and its neighbourhood is characterized by the corresponding texture unit. This paper describes new statistical approaches for texture segmentation, based on minimum and maximum of fuzzy left and right texture unit matrix. In these methods, the “local” texture information for a given pixel and its neighbourhood is characterized by the corresponding fuzzy texture unit. The proposed Minimum Fuzzy Left and Right Texture Unit Matrix (MFLRTU) and Maximum Fuzzy Left and Right Texture Unit Matrix (MXFLRTU) segmentation methods overcome the computational complexity of Fuzzy Texture Unit (FTU) by reducing the texture unit from 2020 to 79. The proposed schemes are compared with the Wavelet Transform with Image Fusion (WTIF) in [20]. The results demonstrate the efficacy of the proposed methods.
关键词：Fuzzy Texture unit; Left Right Texture Unit;Matrix; Texture Spectrum; Texture.