A Method of Online Color-Difference Detecting Based on Image Processing and its Application

2010 ◽  
Vol 37-38 ◽  
pp. 14-17
Author(s):  
Li Jun Zhong ◽  
Wen Wen Li
Keyword(s):  
Image Processing ◽  
Minimum Distance ◽  
Linear Array ◽  
Detection System ◽  
Color Difference ◽  
Experimental Results ◽  
Color Model ◽  
Online Detection ◽  
Ceramic Tiles

A method of the classifying of ceramic tiles’ color difference is proposed, and the online detection system based on linear array color CCD sensors is designed. After the image of tile grabbed by CCD is transformed to the HIS color model, a series of image processing and analyzing methods are used to calculate the eigenvalue of sample. The minimum distance classifier is used to carry out tiles’ classifying. Experimental results show the method is effective.

Application of Object-Based Image Processing Technique in Printing Defect Online Detection

2015 ◽  
Vol 731 ◽  
pp. 210-213
Author(s):  
Shu Feng Liu ◽  
Shao Hong Shen
Keyword(s):  
Image Processing ◽  
Detection Method ◽  
Main Idea ◽  
Color Difference ◽  
Processing Technique ◽  
Experimental Results ◽  
Image Processing Technique ◽  
Online Detection ◽  
Multi Scale ◽  
Color Printing

In this paper ,a color printing defect automatic online detection method based on digital image processing technique is proposed. The main idea of this method is comparison of defect product and template and it makes up of following key models. Firstly, multi-scale segmentation is applied to composed image which is overlaid by detecting product and template image. Secondly, an automatic region similarity analysis calculation is taken to segmentation obtained in multi-scale segmentation. The color difference between detecting product and template can be calculated accurately. Thirdly, defect detection results can be obtained according to threshold segmentation. Finally, the characteristics and advantages are approved by experimental analysis and discussion. Algorithm parameters are adjusted and modified to improve the stability and effectiveness. Experimental results approve that color printing defect automatic detection method in this paper has the characteristics of effectiveness and applicability. And experimental results indicate that this method has the advantage of judging the defect types automatically.

Design of the scanning mode coated glass color difference online detection system

2007 ◽  
Author(s):  
Weihong Bi ◽  
Yu Zhang ◽  
Dajiang Wang ◽  
Baojun Zhang ◽  
Guangwei Fu
Keyword(s):  
Detection System ◽  
Color Difference ◽  
Online Detection ◽  
Coated Glass ◽  
Glass Color

scholarly journals Developing a new color model for image analysis and processing

2007 ◽  
Vol 4 (1) ◽  
pp. 43-55 ◽  
Author(s):  
Rashad Rasras ◽  
Emary El ◽  
Dmitriy Skopin
Keyword(s):  
Image Processing ◽  
Video Processing ◽  
Communication Systems ◽  
Object Identification ◽  
Experimental Results ◽  
Color Model ◽  
Image Process ◽  
Proposed Model ◽  
Model Conversion ◽  
True Color

The theoretical outcomes and experimental results of new color model implemented in algorithms and software of image processing are presented in the paper. This model, as it will be shown below, may be used in modern real time video processing applications such as radar tracking and communication systems. The developed model allows carrying out the image process with the least time delays (i.e. it speeding up image processing). The proposed model can be used to solve the problem of true color object identification Experimental results show that the time spent during RGI color model conversion may approximately four times less than the time spent during other similar models. .

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

Traffic incident detection system based on video image processing

2008 ◽  
Vol 28 (7) ◽  
pp. 1886-1889 ◽  
Author(s):  
Qin WANG ◽  
Shan HUANG ◽  
Hong-bin ZHANG ◽  
Quan YANG ◽  
Jian-jun ZHANG
Keyword(s):  
Image Processing ◽  
Detection System ◽  
Video Image ◽  
Incident Detection ◽  
Traffic Incident ◽  
Video Image Processing

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

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 OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

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