scholarly journals An LBP-Based Active Contour Algorithm for Unsupervised Texture Segmentation

2006 ◽  
Author(s):  
M.A. Savelonas ◽  
D.K. Iakovidis ◽  
D.E. Maroulis
Keyword(s):  
Active Contour ◽  
Texture Segmentation

Active Contour Model with Edge Flow Vector for Texture Segmentation

2015 ◽  
Vol 781 ◽  
pp. 511-514
Author(s):  
Tanunchai Boonnuk ◽  
Sanun Srisuk ◽  
Thanwa Sripramong
Keyword(s):  
Medical Imaging ◽  
Active Contour ◽  
Active Contour Model ◽  
Texture Segmentation ◽  
Gradient Vector Flow ◽  
Gradient Vector ◽  
Texture Image ◽  
Contour Model ◽  
Flow Vector ◽  
Edge Flow

In this paper, we propose effective method for texture segmentation using active contour model with edge flow vector. This technique was applied from previous active contour model that uses gradient vector flow as external force. It was observed that our method provided better results for texture segmentation while a traditional active contour model and active contour model with gradient vector flow were not capable to be used with texture image. Thus, texture image such as medical imaging can be identified using active contour model with edge flow vector.

Texture Segmentation of Natural Images Based on Active Contour Model

2012 ◽  
Vol 546-547 ◽  
pp. 553-558
Author(s):  
Zhan Wang ◽  
Yun Hui Yan ◽  
De Wei Dong ◽  
Ke Chen Song
Keyword(s):  
Level Set ◽  
Active Contour ◽  
Active Contour Model ◽  
Texture Synthesis ◽  
Texture Features ◽  
Texture Segmentation ◽  
Natural Images ◽  
Contour Model ◽  
Signal Features ◽  
Environmental Image

To segment complex texture natural environment images; the first, the texture features of natural images should be analysed and the texture features should be extracted; The second, texture images segmengtation can be achieved by using Mumford-Shah active contour model, this segmentation model can better process fuzzy, default boundary, and this model can be solved by level set method. This method can express well complex texture signal features of natural images. Through making texture segmentation experiment for standard texture synthesis image and natural environmental image, its results show that the texture segmentation based on Mumford-Shah active contour model can segment natural images.

Parametric active contour model using Gabor balloon energy for texture segmentation

2015 ◽  
Vol 10 (2) ◽  
pp. 351-358 ◽  
Author(s):  
Payman Moallem ◽  
Homa Tahvilian ◽  
S. Amirhassan Monadjemi
Keyword(s):  
Active Contour ◽  
Active Contour Model ◽  
Texture Segmentation ◽  
Contour Model

Machine Learning for Texture Segmentation and Classification of Comic Image in SVG Compression

2017 ◽  
Vol 8 (3) ◽  
pp. 37-52
Author(s):  
Ray-I Chang ◽  
Chung-Yuan Su ◽  
Tsung-Han Lin
Keyword(s):  
Active Contour ◽  
Active Contour Model ◽  
Texture Segmentation ◽  
Perceptual Quality ◽  
Support Vector ◽  
File Size ◽  
Model Combining ◽  
Segmentation Accuracy ◽  
Gt Element

Raster comic would result in bad quality while zooming in/out. Different approaches were proposed to convert comic into vector format to resolve this problem. The authors have proposed methods to vectorize comic contents to provide not only small SVG file size and rendering time, but also better perceptual quality. However, they do not process texture in the comic images. In this paper, the authors improve their previously developed system to recognize texture elements in the comic and use these texture elements to provide better compression and faster rendering time. They propose texture segmentation techniques to partition comic into texture segments and non-texture segments. Then, the <pattern> element of SVG is applied to represent texture segments. Their method uses CSG (Composite Sub-band Gradient) vector as texture descriptor and uses SVM (Support Vector Machine) to classify texture area in the comic. Then, the ACM (Active Contour Model) combining with CSG vectors is introduced to improve the segmentation accuracy on contour regions. Experiments are conducted using 150 comic images to test the proposed method. Results show that the space savings of our method is over 66% and it can utilize the reusability of SVG syntax to support comic with multiple textures. The average rendering time of the proposed method is over three times faster than the previous methods. It lets vectorized comics have higher performance to be illustrated on modern e-book devices.

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