Modeling And Implementation Of Multi-scale Morphological Palm Recognition System

In today's society,with the rapid development and application of technologies such as big data,cloud computing,and 5G communications,networks are becoming more and more informatized and intelligent,and technologies for rapid identification of personal identities are emerging one after another.As a biological characteristic of the human body's inherent attributes,the palm of the hand has become the main research object in the field of biological recognition technology due to its good stability and uniqueness.Palm recognition technology can well overcome the shortcomings of traditional identification technology such as easy cracking and easy copying,and it is a frontier subject that has developed rapidly in recent years.It mainly covers many research fields such as artificial intelligence,video and palmprint image processing,pattern recognition and intelligent systems.It has attracted great attention from academic circles,national governments,enterprises and institutions,and has good development potential and broad application prospects.The palm image is mainly composed of the epidermis on the inner surface of the human palm,as well as the main ridges,wrinkles and lines.It has the advantages of rich texture feature information,high stability and continuous reliability.In the multi-scale morphological palm recognition system,it has more typical characteristics of diversity.Its scale selection is closely related to palm recognition technology.Palm images in the civilian field generally have relatively low resolution,and its acquisition equipment is cost-effective and user-acceptable,which is convenient for market development and promotion.Palm recognition is to use the effective area of interest on the palm image to extract the texture,contour,size,proportion and other feature information of the palm image,and verify the similarity with the palm texture feature database based on these feature information,so as to achieve the purpose of identity recognition.If the palm feature information is interactively retrieved with specialized databases in special fields,combined with the palm texture database based on the theory of hand diagnosis in traditional Chinese medicine,it is possible to diagnose and predict physical health based on the palm texture characteristics.The performance of the palm recognition system depends on many aspects such as a complete system architecture,strong hardware support,efficient software algorithms,and secure encryption technology.This paper mainly proposes a model of the palm recognition system based on the Internet of Things(Io T)technology,and proposes a design algorithm to analyze the modeling and implementation of the multi-scale morphological palm recognition system algorithm.The system integrates technologies such as Internet of Things technology,multi-scale analysis,feature fusion,digital morphology,and multi-scale morphology.This paper combines multi-scale analysis to enhance the palm image.The recognition algorithm mainly combines scale function,wavelet function,contourlet and wavelet transform(WT)for analysis and recognition,constructs discrete domain filters,and iteratively directional filter bank performs multi-scale and multi-directional The palm image is broken down.Morphological palm image processing,through feature extraction methods such as structure,time domain,frequency domain,subspace,and statistics.Combining mathematical morphology,binary morphology,edge morphology,etc.,under different scales,morphological features are extracted to form feature vectors,and morphological system modeling is performed.