scholarly journals Steganography of Quantum Color Images Based on Blocking and Gray Level Difference

2020 ◽  
Vol 13 (1) ◽  
pp. 98-105
Author(s):  
Gaofeng Luo ◽  
Ling Shi ◽  
Ammar Oad ◽  
Liang Zong
Keyword(s):  
Color Images ◽  
Gray Level ◽  
Level Difference

scholarly journals Morphological sharpening of color images

2016 ◽  
Vol 64 (1) ◽  
pp. 103-113
Author(s):  
S. Skoneczny
Keyword(s):  
Color Images ◽  
Total Order ◽  
Experimental Results ◽  
Morphological Operations ◽  
Gray Level ◽  
Low Contrast ◽  
Novel Approach ◽  
Multivalued Images ◽  
Theoretical Considerations ◽  
Gray Level Images

Abstract This paper presents a novel approach to morphological contrast sharpening of image using the multilevel toggle operator. The concept presented here is a generalization of toggle based contrast operator for gray-level images. The multilevel toggle operator is used to enhance the contrast of multivalued images. In order to perform necessary morphological operations the modified pairwise ordering (MPO) algorithm is proposed. It gives the total order of color pixels. For comparison four other ordering methods are used. The main advantage of the proposed sharpener is its significant contrast enhancing ability when using MPO. Theoretical considerations as well as practical results are shown. Experimental results show its applicability to low-contrast color images.

scholarly journals Using Color and Texture Feature Extraction Technique to Retrieve Image

2019 ◽  
Vol 8 (11S) ◽  
pp. 915-917
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Texture Feature ◽  
Color Images ◽  
Color Histogram ◽  
Gray Level ◽  
Texture Feature Extraction ◽  
Color Feature ◽  
Occurrence Matrix ◽  
Feature Extraction Technique

This paper proposes a content image retrieval using the texture and the color feature of the images. Although for extraction of texture feature, the “gray level co-occurrence matrix (GLCM) algorithm” is used and for extracting color feature the color histogram is used. The presented system is tested on the WANG database that contains a thousand color images with ten different classes by the help of three various type of distances

scholarly journals Image Texture Feature Extraction Method Based on Regional Average Binary Gray Level Difference Co-occurrence Matrix

2011 ◽  
Vol 10 (3) ◽  
pp. 73-79 ◽  
Author(s):  
Jian Yang ◽  
Jingfeng Guo
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Texture Feature ◽  
Local Area ◽  
Image Texture ◽  
Gray Level ◽  
Texture Feature Extraction ◽  
Feature Extraction Method ◽  
Level Difference ◽  
Occurrence Matrix

Texture feature is a measure method about relationship among the pixels in local area, reflecting the changes of image space gray levels. This paper presents a texture feature extraction method based on regional average binary gray level difference co-occurrence matrix, which combined the texture structural analysis method with statistical method. Firstly, we calculate the average binary gray level difference of eight-neighbors of a pixel to get the average binary gray level difference image which expresses the variation pattern of the regional gray levels. Secondly, the regional co-occurrence matrix is constructed by using these average binary gray level differences. Finally, we extract the second-order statistic parameters reflecting the image texture feature from the regional co-occurrence matrix. Theoretical analysis and experimental results show that the image texture feature extraction method has certain accuracy and validity

scholarly journals Performance Inspection of Gray-Level Difference Method Using Standard Images

1998 ◽  
Vol 18 (Supplement1) ◽  
pp. 75-78
Author(s):  
Akikazu KAGA ◽  
In-Seop Lee ◽  
Yoshio Inoue ◽  
Katsuhito Yamaguchi ◽  
Oh-Sung Kwon
Keyword(s):  
Difference Method ◽  
Gray Level ◽  
Level Difference ◽  
Performance Inspection
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