A Fast Image Cutout Tool Based on Gaussian Mixture Model and Region Growing
碩士 === 國立交通大學 === 資訊科學與工程研究所 === 101 === In this thesis a fast and accurate image cutoff method is developed. The method enables the users to clip object of interest out of an image, which is a useful tool for various applications such as image composition and/or editing. The proposed method represe...
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ndltd-TW-101NCTU53941192016-05-22T04:33:53Z http://ndltd.ncl.edu.tw/handle/79543475821069297899 A Fast Image Cutout Tool Based on Gaussian Mixture Model and Region Growing 建構於高斯混合模型和區域成長的快速物件擷取工具 Chen, Ting-Pu 陳定樸 碩士 國立交通大學 資訊科學與工程研究所 101 In this thesis a fast and accurate image cutoff method is developed. The method enables the users to clip object of interest out of an image, which is a useful tool for various applications such as image composition and/or editing. The proposed method represents the colors of an input image in Gaussian Mixture Model, and designs an iterative region growing based segmentation algorithm to draw out the target object. The proposed scheme has the following advantages: (1) the level of user interaction is low. The cut out operation is accomplished through simply drawing a rectangle encompassing the target object, and (2) the extracted objects are well-tailored. Both object with explicit contour and object with complicate contour can be extracted accurately. The proposed scheme is implemented and compared with the efficient object extraction method – the GrapCut. Experiment results show the proposed method exhibits higher performance than the GrapCut, both in the completeness of the extracted object and the computation time. Lin, Ja-Chen Wang, Ran-Zan 林志青 王任瓚 2013 學位論文 ; thesis 32 en_US |
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碩士 === 國立交通大學 === 資訊科學與工程研究所 === 101 === In this thesis a fast and accurate image cutoff method is developed. The method enables the users to clip object of interest out of an image, which is a useful tool for various applications such as image composition and/or editing. The proposed method represents the colors of an input image in Gaussian Mixture Model, and designs an iterative region growing based segmentation algorithm to draw out the target object. The proposed scheme has the following advantages: (1) the level of user interaction is low. The cut out operation is accomplished through simply drawing a rectangle encompassing the target object, and (2) the extracted objects are well-tailored. Both object with explicit contour and object with complicate contour can be extracted accurately. The proposed scheme is implemented and compared with the efficient object extraction method – the GrapCut. Experiment results show the proposed method exhibits higher performance than the GrapCut, both in the completeness of the extracted object and the computation time.
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Lin, Ja-Chen |
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Lin, Ja-Chen Chen, Ting-Pu 陳定樸 |
author |
Chen, Ting-Pu 陳定樸 |
spellingShingle |
Chen, Ting-Pu 陳定樸 A Fast Image Cutout Tool Based on Gaussian Mixture Model and Region Growing |
author_sort |
Chen, Ting-Pu |
title |
A Fast Image Cutout Tool Based on Gaussian Mixture Model and Region Growing |
title_short |
A Fast Image Cutout Tool Based on Gaussian Mixture Model and Region Growing |
title_full |
A Fast Image Cutout Tool Based on Gaussian Mixture Model and Region Growing |
title_fullStr |
A Fast Image Cutout Tool Based on Gaussian Mixture Model and Region Growing |
title_full_unstemmed |
A Fast Image Cutout Tool Based on Gaussian Mixture Model and Region Growing |
title_sort |
fast image cutout tool based on gaussian mixture model and region growing |
publishDate |
2013 |
url |
http://ndltd.ncl.edu.tw/handle/79543475821069297899 |
work_keys_str_mv |
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