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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/49260

Title: 使用直方圖自適應模糊化和空間資訊的影像分割
Image Segmentation Using Histogram Adaptive Fuzzification and Spatial Information
Authors: Lai, Wen-Jui
Contributors: NTOU:Department of Computer Science and Engineering
Keywords: 模糊测度;模糊集合;直方圖閾值;影像分割
Fuzzy measures;fuzzy sets;histogram thresholding;image segmentation
Date: 2014
Issue Date: 2018-08-22T06:56:04Z
Abstract: 在本篇論文中,我們使用了兩個平滑技術加上模糊自適應分群來分割低品質圖像。使用模糊自適應分群來分割圖片,當輸入的影像有較高的雜訊,分割出來的圖片會有較高百分比的分類錯誤。本文提出的方法可以在過程中先消除輸入影像的雜訊再對影像進行分割就可以減少圖片分割後的分類錯誤。從實驗結果來看,建議方法與模糊自適應分群相比,在輸入低於25dB的影像我們得到更好的圖片分割正確率。
In this paper, we use two smoothing techniques to segment images with noises. Using fuzzy adaptive clustering [1], the segmented image has high misclassification when the input image has significant noises. The proposed methods can remove the noises of input image and reduce the misclassification of segmented image. From the experimental results, compared with HAF, we can find that the proposed methods can reduce the percentage of error of segmented image when the PSNR of input image is less than 25dB.
URI: http://ethesys.lib.ntou.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=G0010157003.id
Appears in Collections:[資訊工程學系] 博碩士論文

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