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

2011 ◽  
Vol 38 (12) ◽  
pp. 15172-15182 ◽  
Author(s):  
Na Dong ◽  
Chun-Ho Wu ◽  
Wai-Hung Ip ◽  
Zeng-Qiang Chen ◽  
Ching-Yuen Chan ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Template Matching ◽  
Multiple Template

Development of a multiple-template matching technique for removal of false positives in a computer-aided diagnostic scheme

2001 ◽  
Author(s):  
Qiang Li ◽  
Shigehiko Katsuragawa ◽  
Roger M. Engelmann ◽  
Samuel G. Armato III ◽  
Heber MacMahon ◽  
...  
Keyword(s):  
Template Matching ◽  
False Positives ◽  
Computer Aided ◽  
Matching Technique ◽  
Multiple Template

scholarly journals Automatic identification of resting state networks: an extended version of multiple template-matching

2015 ◽  
Author(s):  
Javier Guaje ◽  
Juan Molina ◽  
Jorge Rudas ◽  
Athena Demertzi ◽  
Lizette Heine ◽  
...  
Keyword(s):  
Resting State ◽  
Template Matching ◽  
Automatic Identification ◽  
Extended Version ◽  
Resting State Networks ◽  
Multiple Template

scholarly journals Face Recognition using Fast GA

2019 ◽  
Vol 8 (4) ◽  
pp. 12888-12891
Keyword(s):  
Genetic Algorithm ◽  
Template Matching ◽  
Nodal Point ◽  
Mathematical Practice ◽  
Vital Role ◽  
Terminal Condition ◽  
Computational Time ◽  
Face Identification ◽  
Identification System ◽  
The Face

Face Identification System using a fast genetic algorithm computation (FGA) is presented. FGA is used to compute and search the face in a database. The objective of the work is to make a face identification system which can recognize face from a given image or any other image streaming system like webcam. The system also has to detect the face from a system accurately in order to identify the face accurately. The image can be captured either from a proposed webcam or a captured JPEG or PNG image or any other data source. The system needs training with adequate sample images to perform this operation. Training the generic system plays a vital role in identifying the face in an image. A tolerance is identified as a limit to the genetic algorithm which acts as a terminal condition to the evolution. A unique encoding is used which stores the facial features of a human face into numeric string which can be stored and searched with much ease thereby decreasing the search and computational time. Template matching technique is applied to identify the face in a big picture. Generation of an Eigen face is obtained by the stage a mathematical practice called PCA. Eigen Features is also computed such that the measurement of facial metrics is done using nodal point measurement.

scholarly journals Multi-Template Matching: a versatile tool for object-localization in microscopy images

2019 ◽  
Author(s):  
Laurent S. V. Thomas ◽  
Jochen Gehrig
Keyword(s):  
Template Matching ◽  
Object Localization ◽  
Source Codes ◽  
Biological Objects ◽  
Versatile Tool ◽  
Microscopy Images ◽  
Multiple Template ◽  
Automatic Localization

AbstractWe implemented multiple template matching as both a Fiji plugin and a KNIME workflow, providing an easy-to-use method for the automatic localization of objects of interest in images. We demonstrate its application for the localization of entire or partial biological objects. The Fiji plugin can be installed by activating the Multi-Template-Matching and IJ-OpenCV update sites. The KNIME workflow can be downloaded from nodepit space or the associated GitHub repository. Python source codes and documentations are available on the following GitHub repositories: LauLauThom/MultiTemplateMatching and LauLauThom/MultipleTemplateMatching-KNIME.

Lost Property Detection by Template Matching using Genetic Algorithm and Random Search

2015 ◽  
Vol 3 (2) ◽  
pp. 59-64
Author(s):  
Takako Ikuno ◽  
Momoyo Ito ◽  
Shin-ichi Ito ◽  
Minoru Fukumi
Keyword(s):  
Genetic Algorithm ◽  
Template Matching ◽  
Random Search
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