The Research And Implementation Of Colloidal Gold Strip Recognition Method

Medical development has always been a hot topic drawing people's attention,and the appearance of testing strips brings people lots of convenience.The medical strips have been coped with different kinds of chemicals,which could rapidly react with saliva,blood and urine etc.,producing a certain substance with a certain red color which represents the amount of the material reacting with the certain medical substance.But,observations by eyes are not accurate and the amount of the detected substance cannot be detected.Therefore,it is necessary to develop this recognition system for strips and it will promote the popularization of testing strips,accelerating the advancement of medical treatment.The recognition of strips has developed from fuzzy recognition for decades and there are some devices in the market,which are detecting for a certain substance but not for common material.Thus,the universality of recognition system is consequent for the development of medical treatment.The aim is to study the recognition methods for strips and four main subjects will be described in this paper as the following:(1)To give an overview of the developments and applications of immune colloidal gold technique and the domestic and overseas study actuality briefly.(2)To delineate a projection method for recognition of strips and give a certain value of a testing strip.Compared with common methods,the demonstration shows that this method is superior to others in efficiency and accuracy.(3)To introduce an edge detection method based on adjacent dispersion,which is a basic tool to cope with multi-strips,to extract the contour of the strips respectively.The simulation results show that this method has advantages in main edges,comparing with other methods.(4)In this part,the design and implementation and the main modules of recognition system is described.The implementation of recognition system gives a numerical result of the tested strip,and the implementation will facilitate the medical system,offering large numbers of data for disease prediction.The implementation of the disease prediction will effectively prevent the disease from spreading.