scholarly journals Color-Texture Image Watermarking Algorithm Based on Texture Analysis

2013 ◽  
Vol 18 (4) ◽  
pp. 35-43
Author(s):  
Myeongsu Kang ◽  
Truc Kim Thi Nguyen ◽  
Dinh Van Nguyen ◽  
Cheol-Hong Kim ◽  
Jong-Myon Kim
Keyword(s):  
Texture Analysis ◽  
Image Watermarking ◽  
Texture Image ◽  
Color Texture

scholarly journals WRITER IDENTIFICATION BY TEXTURE ANALYSIS BASED ON KANNADA HANDWRITING

2012 ◽  
pp. 80-85
Author(s):  
B.V. DHANDRA ◽  
VIJAYALAXMI.M. B ◽  
GURURAJ MUKARAMBI ◽  
MALLIKARJUN. HANGARGE
Keyword(s):  
Texture Analysis ◽  
Identification Problem ◽  
Document Image ◽  
Independent Method ◽  
Gray Level ◽  
Writer Identification ◽  
Texture Image ◽  
Major Research ◽  
Gabor Filtering ◽  
Occurrence Matrix

Writer identification problem is one of the important area of research due to its various applications and is a challenging task. The major research on writer identification is based on handwritten English documents with text independent and dependent. However, there is no significant work on identification of writers based on Kannada document. Hence, in this paper, we propose a text-independent method for off-line writer identification based on Kannada handwritten scripts. By observing each individual’s handwriting as a different texture image, a set of features based on Discrete Cosine Transform, Gabor filtering and gray level co-occurrence matrix, are extracted from preprocessed document image blocks. Experimental results demonstrate that the Gabor energy features are more potential than the DCTs and GLCMs based features for writer identification from 20 people.

Texture Stationarity Evaluation with Local Wavelet Spectrum

2020 ◽  
Vol 2020 (1) ◽  
pp. 24-27
Author(s):  
Michele Conni ◽  
Hilda Deborah
Keyword(s):  
Wavelet Transform ◽  
Texture Analysis ◽  
Fundamental Property ◽  
Standard Test ◽  
Wavelet Spectrum ◽  
Texture Image ◽  
Stationary Wavelet Transform

In texture analysis, stationarity is a fundamental property. There are various ways to evaluate if a texture image is stationary or not. One of the most recent and effective of these is a standard test based on non-decimated stationary wavelet transform. This method permits to evaluate how stationary is an image depending on the scale considered. We propose to use this feature to characterize an image and we discuss the implication of such approach.

Identification of Wool and Cashmere Based on Texture Analysis

2015 ◽  
Vol 671 ◽  
pp. 385-390 ◽  
Author(s):  
Sen Lin Yuan ◽  
Kai Lu ◽  
Yue Qi Zhong
Keyword(s):  
Neural Network ◽  
Mathematical Modeling ◽  
Texture Analysis ◽  
Texture Feature ◽  
Digital Camera ◽  
Texture Image ◽  
Feasible Method ◽  
Microscopic Images ◽  
Texture Parameters ◽  
Network Experiment

In order to separate wool from cashmere efficiently, an identification method based on texture analysis was proposed in this paper. The microscopic images captured by CCD digital camera were preprocessed as the texture image. Improved Tamura texture feature were employed to analyzing the final texture images and to attaining the texture parameters. Through a large number of samples, the mathematical modeling was completed by using neural network. Experiment results indicate that texture analysis can be a feasible method to identify cashmere and wool.

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