Detecting Repetitive Patterns on Fabrics by Hough Transform
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:  Four edge-featured maps are derived from the input, each being with edges in specific orientation: 0゜, 90゜, 45゜, and 135゜.  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.  Inverse transform the 4 Hough-space maps back to 4 maps in image-space, in which all in-line fragments are respectively recovered.  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.  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  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..
|Appears in Collections:||Thesis|
Files in This Item: