Detecting Repetitive Patterns on Fabrics by Hough Transform
碩士 === 國立交通大學 === 多媒體工程研究所 === 103 === Perception of repetitive imagery patterns is a common experience to all in daily life, the detection of which is useful to many image-oriented applications, and as a result is chosen as the subject of this thesis. It is noted that, in an edge-featured map deriv...
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ndltd-TW-103NCTU56410192016-12-19T04:14:50Z http://ndltd.ncl.edu.tw/handle/52811667233040192552 Detecting Repetitive Patterns on Fabrics by Hough Transform 霍夫空間轉換應用與服裝規律重複性飾紋之偵測 Tsai,Tsung-Lin 蔡宗霖 碩士 國立交通大學 多媒體工程研究所 103 Perception of repetitive imagery patterns is a common experience to all in daily life, the detection of which is useful to many image-oriented applications, and as a result is chosen as the subject of this thesis. It is noted that, in an edge-featured map derived from an image with contents of repetitive patterns, the fragments of edges associated with repetitive-patterned areas appear to lie on the same “line”, which seems to be a general phenomenon through the examination on images in large amounts. Based on such observations, a pilot system exploiting Hough transform for identifying those fragments of edges through which a common line may pass is established. The system operates in 5 steps as follows: [1] Four edge-featured maps are derived from the input, each being with edges in specific orientation: 0゜, 90゜, 45゜, and 135゜. [2] The four maps are transformed into Hough-space, where thresh-holding is taken to select well-responded areas. The transformation is devised in such a way that every image entity in Hough-space is associated with (x, y) coordinates of its counterpart in the image-space. [3] Inverse transform the 4 Hough-space maps back to 4 maps in image-space, in which all in-line fragments are respectively recovered. [4] Clustering of in-line fragments in each of the 4 image-space maps is conducted, where a weighting process is devised so that regions of potential targets may be discerned from uninterested ones via k-mean clustering. [5] A final fusing of the 4 maps of in-lined oriented-fragments, where process of congregating mutual supportive/antagonistic information among 4 maps is performed, concludes the entire process. Initial experiment on a set of images shows encouraging results from the system when extracting repetitive-patterned dresses/fashion where in-lined fragments are relatively close to one another in testing images. As for images of buildings, it is found that refinement of weighting process in [4] is needed for the cases where in-lined fragments appear to be not so tightly located, as shown in such regular architectural structures as window frames and column-and-beam, etc.. Lin,Cheng-Chung 林正中 2014 學位論文 ; thesis 78 zh-TW |
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碩士 === 國立交通大學 === 多媒體工程研究所 === 103 === Perception of repetitive imagery patterns is a common experience to all in daily life, the detection of which is useful to many image-oriented applications, and as a result is chosen as the subject of this thesis.
It is noted that, in an edge-featured map derived from an image with contents of repetitive patterns, the fragments of edges associated with repetitive-patterned areas appear to lie on the same “line”, which seems to be a general phenomenon through the examination on images in large amounts.
Based on such observations, a pilot system exploiting Hough transform for identifying those fragments of edges through which a common line may pass is established. The system operates in 5 steps as follows:
[1] Four edge-featured maps are derived from the input, each being with edges in specific orientation: 0゜, 90゜, 45゜, and 135゜.
[2] The four maps are transformed into Hough-space, where thresh-holding is taken to select well-responded areas. The transformation is devised in such a way that every image entity in Hough-space is associated with (x, y) coordinates of its counterpart in the image-space.
[3] Inverse transform the 4 Hough-space maps back to 4 maps in image-space, in which all in-line fragments are respectively recovered.
[4] Clustering of in-line fragments in each of the 4 image-space maps is conducted, where a weighting process is devised so that regions of potential targets may be discerned from uninterested ones via k-mean clustering.
[5] A final fusing of the 4 maps of in-lined oriented-fragments, where process of congregating mutual supportive/antagonistic information among 4 maps is performed, concludes the entire process.
Initial experiment on a set of images shows encouraging results from the system when extracting repetitive-patterned dresses/fashion where in-lined fragments are relatively close to one another in testing images. As for images of buildings, it is found that refinement of weighting process in [4] is needed for the cases where in-lined fragments appear to be not so tightly located, as shown in such regular architectural structures as window frames and column-and-beam, etc..
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author2 |
Lin,Cheng-Chung |
author_facet |
Lin,Cheng-Chung Tsai,Tsung-Lin 蔡宗霖 |
author |
Tsai,Tsung-Lin 蔡宗霖 |
spellingShingle |
Tsai,Tsung-Lin 蔡宗霖 Detecting Repetitive Patterns on Fabrics by Hough Transform |
author_sort |
Tsai,Tsung-Lin |
title |
Detecting Repetitive Patterns on Fabrics by Hough Transform |
title_short |
Detecting Repetitive Patterns on Fabrics by Hough Transform |
title_full |
Detecting Repetitive Patterns on Fabrics by Hough Transform |
title_fullStr |
Detecting Repetitive Patterns on Fabrics by Hough Transform |
title_full_unstemmed |
Detecting Repetitive Patterns on Fabrics by Hough Transform |
title_sort |
detecting repetitive patterns on fabrics by hough transform |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/52811667233040192552 |
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