Estimating the embedding capacity of a color image using Color Difference

2010 ◽  
Author(s):  
Nagaraj V. Dharwadkar ◽  
B. B. Amberker
Keyword(s):  
Color Image ◽  
Color Difference ◽  
Embedding Capacity

Color image design based on machine learning and SVM algorithm

2020 ◽  
pp. 1-12
Author(s):  
Li Bo
Keyword(s):  
Image Processing ◽  
Graphic Design ◽  
Management System ◽  
Computer Network ◽  
Color Image ◽  
Color Difference ◽  
Color Management ◽  
Development Mode ◽  
Operation Process ◽  
Svm Algorithm

In today’s society, graphic design, as a popular image processing technology, plays an increasingly important role in people’s lives. In the specific operation process of graphic design, It is no longer restricted to the traditional development mode, such as file format and other factors. With the development of computer network technology, people promote the development of graphic design by constructing color management system. At the same time, the construction of color management system can help people to change colors and define colors when they process image information and output pictures. In the process of printing pictures, in order to make the colors used in the design process clearly printed out and without color difference, there are still many problems to be considered. First, we need to consider the unexpected situation and the complexity of image processing. Based on the introduction of computer learning, this paper will discuss and study the development of graphic design by SVM theory.

scholarly journals A secure image steganography based on burrows wheeler transform and dynamic bit embedding

2019 ◽  
Vol 9 (1) ◽  
pp. 460
Author(s):  
Ahmed Toman Thahab
Keyword(s):  
Communication Networks ◽  
Color Image ◽  
Image Steganography ◽  
Digital Data ◽  
Embedding Capacity ◽  
Image Size ◽  
Secret Data ◽  
Exclusive Or ◽  
Burrows Wheeler Transform ◽  
Color Image Steganography

In modern public communication networks, digital data is massively transmitted through the internet with a high risk of data piracy. Steganography is a technique used to transmit data without arousing suspicion of secret data existence.  In this paper, a color image steganography technique is proposed in spatial domain. The cover image is segmented into non-overlapping blocks which are scattered among image size window using Burrows Wheeler transform before embedding. Secret data is embedded in each block according to its sequence in the Burrows Wheeler transform output. The hiding method is an operation of an exclusive-or between a virtual bit which is generated from the most significant bit and the least significant bits of the cover pixel. Results of the algorithm are analyzed according to its degradation of the output image and embedding capacity. The results are also compared with other existing methods.

Pattern edge color difference in a color image sensor with a GRIN rod lens

1990 ◽  
Vol 29 (28) ◽  
pp. 4081 ◽  
Author(s):  
Kazutake Uehira ◽  
Kazumi Komiya
Keyword(s):  
Color Image ◽  
Color Difference ◽  
Image Sensor

scholarly journals Protein Concentration Determination in Latex Glove Using Biocompatibility Morphological Mean Test

2020 ◽  
Vol 2 ◽  
pp. 18-24
Author(s):  
Toa C. K. ◽  
Sim K. S. ◽  
Chan Y. K.
Keyword(s):  
Protein Concentration ◽  
Color Image ◽  
Protein Detection ◽  
Color Difference ◽  
Worst Case ◽  
Latex Glove ◽  
Standard Curve ◽  
Latex Gloves ◽  
Threatening Condition ◽  
Life Threatening

Latex gloves are seen as an indispensable item in the healthcare field because it offers superior protection for both the medical staff and patient against harmful substances. However, latex gloves with high protein concentration have a high possibility to induce latex allergy which in the worst case can lead to a life-threatening condition. To minimize the occurrence of an allergy reaction, the computerized Biocompatibility Morphological Mean (BMM) test for protein detection is proposed. This test initially goes through the chemical process to determine the protein that resides in the glove sample. After that, the sample is electronically converted into a digital image. Finally, the image undergoes color image processing for calculating the color difference values. These values are then plotted on a standard curve. A high correlation coefficient (R2>0.97) of the standard curve gives better accuracies. The proposed method only takes about 40 minutes to complete the test, while existing methods need at least 6 hours.

Extending the Visibility of Dichromats Using Histogram Equalization of Hue Value Defined for Dichromats

2019 ◽  
Vol 19 (03) ◽  
pp. 1950016 ◽  
Author(s):  
Daisuke Miyazaki ◽  
Sayaka Taomoto ◽  
Shinsaku Hiura
Keyword(s):  
Color Image ◽  
Color Difference ◽  
Histogram Equalization ◽  
Green Color ◽  
Experimental Section ◽  
Cone Cells

Dichromats lack one of the three cone cells, which detects red, green, and blue lights. For example, red-green color blinds cannot distinguish the color between red, yellow, and green. In order to extend the ability of dichromats to recognize the color difference, we proposed a method to expand the color difference when observed by dichromats. We have defined a hue variable for dichromats and implemented to our algorithm. We applied the histogram equalization to the hue of dichromats in order to enlarge the color difference recognized by dichromats. We have applied our method to RGB color image, and shown its performance at the experimental section.

Sign in / Sign up

Export Citation Format

Share Document