scholarly journals Texture Analysis Methods for Medical Image Characterisation

10.5772/8912 ◽  
2010 ◽  
Author(s):  
William Henry
Keyword(s):  
Texture Analysis ◽  
Medical Image ◽  
Analysis Methods

Wild boar Classification by Using a Fusion of Texture Analysis Methods

2020 ◽  
Author(s):  
Luis C. S. Junior ◽  
Mariceia B. S. Padua ◽  
Leonardo M. Ogusuku ◽  
Marcelo K. Albertini ◽  
Renato Pimentel ◽  
...  
Keyword(s):  
Wild Boar ◽  
Texture Analysis ◽  
Analysis Methods

scholarly journals Local Derivative Vector Pattern: Hybrid Pattern for Content-Based Medical Image Retrieval

2020 ◽  
Vol 7 (4) ◽  
pp. 79-86
Author(s):  
Nagadevi Darapureddy ◽  
Nagaprakash Karatapu ◽  
Tirumala Krishna Battula
Keyword(s):  
Image Retrieval ◽  
Texture Analysis ◽  
Medical Image ◽  
Local Binary Pattern ◽  
Medical Images ◽  
Texture Classification ◽  
Medical Image Retrieval ◽  
Local Vector ◽  
Local Derivative ◽  
Local Derivative Pattern

This paper examines a hybrid pattern i.e. Local derivative Vector pattern and comparasion of this pattern over other different patterns for content-based medical image retrieval. In recent years Pattern-based texture analysis has significant popularity for a variety of tasks like image recognition, image and texture classification, and object detection, etc. In literature, different patterns exist for texture analysis. This paper aims at forming a hybrid pattern compared in terms of precision, recall and F1-score with different patterns like Local Binary Pattern (LBP), Local Derivative Pattern (LDP), Completed Local Binary Pattern (CLBP), Local Tetra Pattern (LTrP), Local Vector Pattern (LVP) and Local Anisotropic Pattern (LAP) which were applied on medical images for image retrieval. The proposed method is evaluated on different modalities of medical images. The results of the proposed hybrid pattern show biased performance compared to the state-of-the-art. So this can further extended with other pattern to form a hybrid pattern.

Rice Paper Classification Study Based on Signal Processing and Statistical Methods in Image Texture Analysis

2014 ◽  
Vol 2 (3) ◽  
pp. 1-14
Author(s):  
Haotian Zhai ◽  
Hongbin Huang ◽  
Shaoyan He ◽  
Weiping Liu
Keyword(s):  
Texture Analysis ◽  
Classification Accuracy ◽  
Image Texture ◽  
Analysis Method ◽  
Classification Result ◽  
Image Texture Analysis ◽  
Analysis Methods ◽  
Paper Classification ◽  
Regular Texture ◽  
Better Than

Texture analysis plays an important role in image processing. In the field of texture analysis, the regular texture has been studied a lot, but the natural texture with complex backgrounds is less studied. This paper brings texture analysis into the study of rice paper's classification. First of all it shows the processing flow chart of rice paper classification. By comparing the different kinds of texture analysis methods it chooses the LAWS texture method and uncertainty texture spectrum method to achieve the rice paper classification. When it uses the two texture analysis methods separately, the classification accuracy of rice paper is lower, so it tries to combine the two texture analysis methods. The experimental results show that the classification result got with two combined texture analysis methods is better than that got with one single texture analysis method. The classification accuracy of rice paper has been distinctly improved after the combination of the two texture analysis methods.

Polar Coordinates Texture Analysis Methods for Digitized Intravascular Images

1996 ◽  
pp. 303-306
Author(s):  
I. Hardouin ◽  
E. Lieback ◽  
J. Armbruster ◽  
J. Boksch ◽  
M. Schartl ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Polar Coordinates ◽  
Analysis Methods
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