The Research Of Indoor Location System Based On Image Recognition

In recent years,the technology of image information recognition and processing has been paid more and more attention.There are more and more achievements in academic research.It has been widely used in daily life scene,industry,medicine,aerospace and so on.Image information recognition Technology still has a lot of potential applications and research significance.At the same time,since the 21 st century,including Apple,Samsung and major domestic mobile phone manufacturers of smart phone products,image acquisition performance and computing power of the rapid growth and the popularity of mobile smart phone devices,people increasingly rely on mobile phones such equipment to provide Various services.This paper analyzes the use of smart phones in the case of public buildings,such as shopping malls,the location that is very limited,and the indoor GPS signal is not received,through the use of smart phones to achieve indoor positioning function has become a popular application scenarios.In the image localization algorithm based on image information recognition,image matching algorithm is the most critical step in image information recognition algorithm.The rate of image matching technology and matching success rate are the important factors that affect the image reliability.This paper draws on the positioning system model used in the "Image processing-based urban environment positioning research" of the University of Berkeley,and puts forward the positioning system model which is more suitable for the indoor environment and the relatively efficient solution.According to this scenario,this paper presents a series of solutions,the main research direction has the following aspects.This paper analyzes the theoretical methods and implementation methods of SIFT and SURF in detail,and compares and analyzes the advantages and disadvantages of using SIFT and SURF directly for the scene characteristics of indoor environment.The vector space model is proposed based on the SURF feature matching,and the support vector machine algorithm is introduced to realize the classification of the image.The position of the matching image is marked on the map,and the indoor positioning system is realized.The advantages and disadvantages of the system based on SURF eigenvalue matching and vector space model classifier system are compared and analyzed in detail.The results show that the SURF feature matching algorithm and the vector space model are classified by experimentsThe system has a good performance in matching rate and registration rate in indoor positioning applications.In this paper,the indoor positioning system based on image information recognition is studied.According to the characteristics of indoor application scene,a vector space model classification system based on SURF is proposed,and the advantages of matching system based on SURF feature are analyzed in detail.The simulation experiment is carried out to prove its accuracy and timeliness.