Two Step Template Matching Method with Correlation Coefficient and Genetic Algorithm

Abstract - Biometrics is the study of automatic methods for recognizing humans based on one or more parts of the human body that are unique. One human characteristic that can be used is iris, iris features can be used as distinguishing characteristics with other individuals. The stage that the writer did to be able to recognize the iris pattern of someone's eye in a digital image was the pre-processing stage, the template saving stage and the matching stage. In this study the author applies the template matching method to store the image into a template image stored in the database and the algorithm correlation coefficient for the characteristic matching algorithm between template data and test data. The application is designed using the Matlab R2010a programming language. The results of testing 22 images obtained by the percentage of system success was 86.36%. Keywords - Iris, Template Matching, Correlation Coefficient

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A Template Matching Method Based on Genetic Algorithm Optimization

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.220-223.1298 ◽

2012 ◽

Vol 220-223 ◽

pp. 1298-1302 ◽

Cited By ~ 1

Author(s):

Xiao Hui Zhang ◽

Qing Liu ◽

Mu Li

Keyword(s):

Genetic Algorithm ◽

Real Time ◽

Template Matching ◽

Fitness Function ◽

Image Process ◽

Algorithm Optimization ◽

Matching Method ◽

Correlation Degree ◽

Degree Function ◽

Effective Performance

This paper presents a method of using Genetic Algorithm (GA) to optimize template and image searching process, using template matching to recognize target. An initial matching template is set manually according to 2D shape and the optimizing template is obtained by GA optimizing to meet the requirement of real-time and effective performance. Then the pixel position is encoded into genes, template correlation degree function works as fitness function to do GA search to recognize the target. The relating image process experiments show that this method has good real-time and robustness performance.

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An improved species based genetic algorithm and its application in multiple template matching for embroidered pattern inspection

Expert Systems with Applications ◽

10.1016/j.eswa.2011.05.085 ◽

2011 ◽

Vol 38 (12) ◽

pp. 15172-15182 ◽

Cited By ~ 15

Author(s):

Na Dong ◽

Chun-Ho Wu ◽

Wai-Hung Ip ◽

Zeng-Qiang Chen ◽

Ching-Yuen Chan ◽

...

Keyword(s):

Genetic Algorithm ◽

Template Matching ◽

Multiple Template

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Patent Innovation Factors Evolution Based on P-SVM and GCCA

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.39.247 ◽

2010 ◽

Vol 39 ◽

pp. 247-252

Author(s):

Sheng Xu ◽

Zhi Juan Wang ◽

Hui Fang Zhao

Keyword(s):

Genetic Algorithm ◽

Support Vector Machines ◽

Correlation Coefficient ◽

Network Architecture ◽

Innovation Management ◽

Model Development ◽

Real Data ◽

Support Vector ◽

Vector Machines ◽

Gray Correlation

A two-stage neural network architecture constructed by combining potential support vector machines (P-SVM) with genetic algorithm (GA) and gray correlation coefficient analysis (GCCA) is proposed for patent innovation factors evolution. The enterprises patent innovation is complex to conduct due to its nonlinearity of influenced factors. It is necessary to make a trade off among these factors when some of them conflict firstly. A novel way about nonlinear regression model with the potential support vector machines (P-SVM) is presented in this paper. In the model development, the genetic algorithm is employed to optimize P-SVM parameters selection. After the selected key factors by the PSVM with GA model, the main factors that affect patent innovation generation have been quantitatively studied using the method of gray correlation coefficient analysis. Using a set of real data in China, the results show that the methods developed in this paper can provide valuable information for patent innovation management and related municipal planning projects.

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A multiple-layer flexible mesh template matching method for non-rigid registration between a pelvis model and CT images

10.1117/12.481354 ◽

2003 ◽

Cited By ~ 4

Author(s):

Jianhua Yao ◽

Russell H. Taylor

Keyword(s):

Template Matching ◽

Ct Images ◽

Matching Method ◽

Rigid Registration ◽

Multiple Layer

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Research on Method of Farmland Obstacle Boundary Extraction in UAV Remote Sensing Images

Sensors ◽

10.3390/s19204431 ◽

2019 ◽

Vol 19 (20) ◽

pp. 4431

Author(s):

Fang ◽

Chen ◽

Jiang ◽

Wang ◽

Liu ◽

...

Keyword(s):

Remote Sensing ◽

Correlation Coefficient ◽

Unmanned Aerial Vehicle ◽

Information Acquisition ◽

Template Matching ◽

Obstacle Detection ◽

Image Resolution ◽

Average Deviation ◽

Actual Measurement ◽

Aerial Vehicle

Aimed at the problem of obstacle detection in farmland, the research proposed to adopt the method of farmland information acquisition based on unmanned aerial vehicle landmark image, and improved the method of extracting obstacle boundary based on standard correlation coefficient template matching and assessed the influence of different image resolutions on the precision of obstacle extraction. Analyzing the RGB image of farmland acquired by unmanned aerial vehicle remote sensing technology, this research got the following results. Firstly, we applied a method automatically registering coordinates, and the average deviations on the X and Y direction were 4.6 cm and 12.0 cm respectively, while the average deviations manually by ArcGIS were 4.6 cm and 5.7 cm. Secondly, with an improvement on the step of the traditional correlation coefficient template matching, we reduced the time of template matching from 12.2 s to 4.6 s. The average deviation between edge length of obstacles calculated by corner points extracted by the algorithm and that by actual measurement was 4.0 cm. Lastly, by compressing the original image on a different ratio, when the pixel reached 735 × 2174 (the image resolution reached 6 cm), the obstacle boundary was extracted based on correlation coefficient template matching, the average deviations of boundary points I of six obstacles on the X and Y were respectively 0.87 and 0.95 cm, and the whole process of detection took about 3.1 s. To sum up, it can be concluded that the algorithm of automatically registered coordinates and of automatically extracted obstacle boundary, which were designed in this research, can be applied to the establishment of a basic information collection system for navigation in future study. The best image pixel of obstacle boundary detection proposed after integrating the detection precision and detection time can be the theoretical basis for deciding the unmanned aerial vehicle remote sensing image resolution.

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Dynamic target template matching for railway catenary suspension motion detection in wind area

International Journal of Distributed Sensor Networks ◽

10.1177/1550147718797956 ◽

2018 ◽

Vol 14 (9) ◽

pp. 155014771879795 ◽

Cited By ~ 1

Author(s):

Wei Zhou ◽

Heting Xiao ◽

Zhonggang Wang ◽

Lin Chen ◽

Shaoqing Fu

Keyword(s):

Template Matching ◽

Three Dimensional ◽

Moving Target ◽

Maximum Relative Error ◽

Gradual Change ◽

Matching Method ◽

Safety Research ◽

Target Template ◽

Target Templates ◽

Dynamic Target

A dynamic target template matching method was proposed to identify railway catenary suspension movements of wind-induced vibration in wind area. Catenary positioning point was taken as the target template, which was compared with equal-sized image sequentially using the proposed matching difference. And, three-dimensional contour map of matching difference value at each sub-area was obtained, where the target pixel coordinates were determined by the minimum matching difference value. Considering the complex imaging condition, the target template was updated by the detected target image to sense the gradual change of illumination conditions like brightness and contrast. Furthermore, to eliminate detecting errors due to wind-induced camera vibration, both static and moving target templates were identified for acquiring the absolute motion of the moving target. Finally, validation test was performed with animation in PowerPoint. The calculated target displacement agrees well with theoretical motion with maximum relative error of 1.8%. And experiment application was conducted at site by analyzing the relationship between detecting displacement and wind speed. Results indicate that the proposed dynamic target template matching method can meet required engineering precision and provide an effective way for wind-vibration safety research of railway catenary system in wind area.

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