Xiao Yun

Bio: Xiao Yun is an academic researcher. The author has contributed to research in topics: Background subtraction & Cluster analysis. The author has an hindex of 1, co-authored 1 publications receiving 2 citations.

Research on Vehicle Detection and Tracking Algorithm Based on the Methods of Frame Difference and Adaptive Background Subtraction Difference

Abstract: This paper proposed methods of vehicle detection and tracking algorithm in real-time traffic. In the detection of realtime moving vehicle, vehicle areas would be determined through road line detection. Then, the main color information of moving and non-moving area would be obtained through frame difference. Filling the main color information in vehicle moving area would lead to a similar background image. At last, moving vehicles would be determined through adaptive Background Subtraction difference. In the tracking of moving vehicles, firstly, all characteristic corners can be got by using Harris detection. Then, all characteristic corner set in the separate moving area would be collected through cluster analysis. For each characteristic individual corner set can generate a circle embracing all characteristics, some problems like vehicle barrier could be analyzed by using the radius of characteristic circle. At last, conduct feature matching tracking by using the center of feature circle. Experimental result shows that the improving algorithm can extract all moving objects, which was endowed with strong background adaptability and better real-time performance. Keywords-target detection; frame difference method; background subtraction difference method; harris corner detection; clustering analysis

Vehicle Detection and Classification: A Review

Abstract: Smart traffic and information systems require the collection of traffic data from respective sensors for regulation of traffic. In this regard, surveillance cameras have been installed in monitoring and control of traffic in the last few years. Several studies are carried out in video surveillance technologies using image processing techniques for traffic management. Video processing of a traffic data obtained through surveillance cameras is an instance of applications for advance cautioning or data extraction for real-time analysis of vehicles. This paper presents a detailed review of vehicle detection and classification techniques and also discusses about different approaches detecting the vehicles in bad weather conditions. It also discusses about the datasets used for evaluating the proposed techniques in various studies.

Novel image retrieval method based on improved K -means algorithm

Abstract: Having analyzed the drawbacks of image retrieval based on K-means algorithm,a novel image retrieval method based on improved K-means algorithm was presented in this paper.Firstly,computed the distance of every two color histograms of all color histograms in the image feature database.Then,took the two feature vectors which the distance between them is the maximum in the database,as the first two initial centroids,and found all correct initial centroids,and clustered according to the initial class centroids.Finally,started image retrieval.Experimental results demonstrate that the proposed method is efficient.