Application Study Of The Image Processing Technology In ITS

Today,image processing technology plays an ever-important role in ITS(Intelligent Transportation System).Applying image processing technology to ITS is a challenging field which has great theoretical significance and practical value.In ITS,image processing technology is applied to a variety of areas such as vision-based intelligent vehicle guidance,vision-based traffic surveillance and vision-based traffic management.In this thesis,we focus on the latter two fields which mainly include moving vehicles segmentation,moving vehicles tracking,shadow detection of moving vehicles and license plate recognition.The main contributions of the thesis are as follows:A novel nonparametric multimodal background model is proposed to segment moving objects.The binned kernel density estimators are exploited to estimate the probability density function of background intensity in training sequence.Based on the gravity center of the data points,the binned kernel density estimators describe the key information of the original whole sample set and avoid the repetition computation in the evaluation phase.Compared with algorithm based on the whole samples,the proposed approach is proved to be efficient in traffic surveillance systems.The Mean-Shift algorithm of the fixed kernel-bandwidth is applied to track vehicle changing big in size with the huge error of size and space localization,and changing small in size with the huge error of size localization.At the same time,the Mean-Shift algorithm,strictly depends on the assumption that object regions overlap between the consecutive frames,is applied to track fast motion objects without converging to real place of objects.Therefore,a object tracking algorithm is proposed,this algorithm gets the target's scale using automatic selection of kernel-bandwidth based on feature matching.At the same time,find the starting position of Mean-Shift iterative through the Feature Matching.Experimental results show that the proposed algorithm can track successfully fast moving objects of changing in size.In order to robustly track the muti-degrees of freedom moving objects in video sequences in the presence of cluttered backgrounds,a tracking algorithm of muti-degrees of freedom moving object is proposed based on the Particle Filter Principle.This algorithm gets the target's scale using automatic selection of kernel-bandwidth based on updating the position of the object and the covariance matrix that describes the shape of the object.Test results tracking various objects in different scenarios show that the proposed algorithm can track muti-degrees of freedom moving objects,and can adapt to change of the object's scale and angle.Cast shadows from moving objects reduce the general ability of robust classification and tracking of these objects,in outdoor surveillance applications.Classic pixel-based object shadow detection algorithm limits the performance,owing to noise.A algorithm for segmentation of cast shadows is proposed with improved accuracy,combining region with illumination invariant.This algorithm takes into account the features of all the pixels in a region.Using EM Cluster,the moving region is segmented into blocks with the smaller blocks combined with the neighbor bigger blocks.Shadow detection is performed in every block based on the illumination invariant between the shadow region and the corresponding background region.Experimental results show that the proposed algorithm is the most robust to noise,can detect accurately shadows and is more efficient than the algorithm based on pixel.A novel approach for license plate location and tilt correction is proposed based on the feature matching of character.Considering that the primacy character of the PRC license plates is Chinese characters,this approach gets the Chinese character's position using standard Chinese characters of the PRC license plates based on feature matching. The Chinese character's position in the PRC license plates holds fixed,thus,the proposed algorithm achieves license plate location and tilt correction using Chinese characters location.To demonstrate the effectiveness of the proposed algorithm,it conducts extensive experiments over a large number of real-world vehicle license plates. It reports that the proposed approach has high accuracy and robustness.The above contributions constitute the main parts of this thesis.The content of this thesis includes the main aspects of image processing technology in ITS.The contributions of this thesis are further development of image processing technology in ITS.The proposed new idea and methods have great guiding significance to the application research of image processing technology in ITS and have greater practical value.