1、外文科技资料翻译 英文原文 Research on a face recognition system by the genetic algorithm Computer vision and recognition is playing anincreasingly important role in modern intelligent control.Object detection is the first and most important step inobjectrecognition.Traditionally,a special object can berecognize
2、d by the template matching method,but the recognition speed has always been a problem.In this article,animproved general genetic algorithm-based face recognitionsystem is proposed.The genetic algorithm(GA)has beenconsidered to be a robust and global searching method.Here,the chromosomes generated by
3、 GA contain the information needed to recognize the object.The purpose of thisarticle is to propose a practical method of face detection andrecognition.Finally,the experimental results,and a comparison with the traditional template matching method,andsome otherconsiderations,are also given. 1 Introd
4、uction If we search on the web or in a conference proceedingsabout intelligent control,lots of papers and applications arepresented.Among them,image processing and recognitionoccupy a very large percentage.The higher the degree ofintelligence,the more important the image detection andrecognition tec
5、hnology. For controlling an intelligent system(autonomous mobile vehicle,robot,etc.),the most important element is thecontrol strategy,but before automatically making it move,image recognition is needed.For an intelligent control system,it is necessary to acquire information about the external world
6、 automatically by sensors,in order to recognize itsposition and the surrounding situation.A camera is one ofthe most important sensors for computer vision.That is tosay,the system endeavors to find out what is in an image(the environment of the robot)taken by the camera:trafficsigns,obstacles,guidel
7、ines,etc. The reliability and time-response of object detection andrecognition have a major influence on the performance andusability of the whole object recognition system.1Thetemplatematching method is a practicable and reasonablemethod for object detection.2This article gives an improvement in th
8、e general template matching method. In addition,in order to search for the object of interestin an image,lots of data need to be processed.The geneticalgorithm(GA)has been considered to be a robust andglobal searching method(although it is sometimes said thatGA can not be used for finding the global
9、optimization3).Here,the chromosomes generated by GA contain information about the image data,and the genetic and evolutionoperations are used to obtain the best match to the template:searching for the best match is the goal of this article.This thought emerged from the features of the GA,andthe need
10、 to recognize the faces of people easily and quicklyby an intelligent system.The single concept and features ofimage processing and the GA will not be introduced here,because there is already extensive literature on this subject. In this article,Sect.2 gives the encoding method of theGA and the expe
11、rimental setting that is used.In Sect.3,theexperiment and the analysis are addressed.Some conclusions are given in Sect.4. Theory and experimental setting For an image recognition system,the most interesting partthat has special features has first to be detected in the original image.This is called
12、object detection.After that,thispart will be compared to a template to see if it is similar ornot.This is called object recognition.For example,if wewant to find a special person in an image,we first have todetect people in the image,and then recognize which one isthe person of interest(sometimes these two steps will beexecuted simultaneously).The whole procedure is shown inFig.1.
