Research And Implementation Of Face Recognition System For Bank Staff Based On Open CV

With the rapid development of information technology and the continuous improvement of people's safety awareness,traditional identification methods are easily stolen and leaked,which is insufficient to meet the needs of the society.Recognition methods based on biological features(such as fingerprints,irises,etc.)have gradually become very hot research areas today.Banks,as a class of industries with higher security requirements,have become the first beneficiaries of this new type of technology.In a wide variety of biometric technologies,face recognition methods are more natural and intuitive,and they are non-contact,non-mandatory,concurrency,and convenience,attracting many researchers to study them.It has been widely used in many fields such as national security,document verification,information security,and personnel attendance.Open CV is a visual library.It is open source and cross-platform.It implements most algorithms for digital image processing and computer vision.It can be directly applied in many fields,including object recognition,image partitioning,face recognition,motion tracking,motion analysis,etc.It can also be used as an ideal tool for professionals to perform secondary development to realize the core algorithm of face recognition.The innovation of this paper lies in the use of embedded technology,the use of micro-camera to collect face images,the control and forwarding of the terminal microprocessor,the transmission of the images to the upper computer server through the wireless local area network,the use of L Shade to optimize the penalty parameter C and kernel parameter G in SVM,and the use of optimized parameters C and G to establish SVM combined with PCA model to classify and identify the face images obtained.If it is detected that the user's identity is illegal,the lower computer will issue an alarm.This article adopts embedded development technology to capture the bank staff's head through a microcontroller-driven network camera,and transmits the bank staff's image information to the host computer's server through the local area network.The application program on the server builds an Open CV development environment.The PCA(Principal Component Analysis,PCA)algorithm trains the facial image training set of the bank staff to form a principal component feature set,and then processes the image stream file captured by the camera as a series of complex information samples.According to the method of principal component analysis,the principal component feature set is formed after dimension reduction by special rules,and then SVM is used to classify the samples.LSHADE algorithm optimizes the model parameters,determines the optimal parameter combination of the model,outputs the recognition rate and transmits it to the lower computer,thus realizing the authentication of bank staff and strengthening the identification.strengthening the bank's security work.Biometrics technology uses techniques such as computer vision,graphic image processing,and pattern recognition to extract and describe human physiological characteristics or behavioral characteristics,thereby verifying whether the user's identity is valid.Through experimental tests,the system has a high recognition rate and practicality.