Sanyuan Zhang

A hybrid method for robust car plate character recognition

Image-based car plate recognition is an indispensable part of an intelligent traffic system. The quality of the images taken for car plates, especially for Chinese car plates, however, may sometimes be very poor, due to the operating conditions and distortion because of poor photographical environments. Furthermore, there exist some similar characters, such as 8 and B, 7 and T and so on. They are less distinguishable because of noises and/or distortions. To achieve robust and high recognition performance, in this paper, a two-stage hybrid recognition system combining statistical and structural recognition methods is proposed. Car plate images are skew corrected and normalized before recognition. In the first stage, four statistical sub-classifiers recognize the input character independently, and the recognition results are combined using the Bayes method. If the output of the first stage contains characters that belong to prescribed sets of similarity characters, structure recognition method is used to further classify these character images: they are preprocessed once more, structure features are obtained from them and these structure features are fed into a decision tree classifier. Finally, genetic algorithm is employed to achieve optimum system parameters. Experiments show that our recognition system is very efficient and robust. As part of an intelligent traffic system, the system has been in successful commercial use.

Reverse innovative design - an integrated product design methodology

Todays product designer is being asked to develop high quality, innovative products at an ever increasing pace. To meet this need, an intensive search is underway for advanced design methodologies that facilitate the acquisition of design knowledge and creative ideas for later reuse. Additionally, designers are embracing a wide range of 3D digital design applications, such as 3D digitization, 3D CAD and CAID, reverse engineering (RE), CAE analysis and rapid prototyping (RP). In this paper, we propose a reverse engineering innovative design methodology called Reverse Innovative Design (RID). The RID methodology facilitates design and knowledge reuse by leveraging 3D digital design applications. The core of our RID methodology is the definition and construction of feature-based parametric solid models from scanned data. The solid model is constructed with feature data to allow for design modification and iteration. Such a construction is well suited for downstream analysis and rapid prototyping. In this paper, we will review the commercial availability and technological developments of some relevant 3D digital design applications. We will then introduce three RE modelling strategies: an autosurfacing strategy for organic shapes; a solid modelling strategy with feature recognition and surface fitting for analytical models; and a curve-based modelling strategy for accurate reverse modelling. Freeform shapes are appearing with more frequency in product development. Since their natural parameters are hard to define and extract, we propose construction of a feature skeleton based upon industrial or regional standards or by user interaction. Global and local product definition parameters are then linked to the feature skeleton. Design modification is performed by solving a constrained optimization problem. A RID platform has been developed and the main RE strategies and core algorithms have been integrated into SolidWorks as an add-in product called ScanTo3D. We will use this system to demonstrate our RID methodology on a collection of innovative consumer product design examples.

Error resilience schemes of H.264/AVC for 3G conversational video services

The emerging of third generation mobile system (3G) makes conversational video transmission in wireless environment possible, and the latest 3GPP/3GPP2 standards suggest 3G terminals support H.264/AVC. Due to high bit error rate in wireless environment, error resilience schemes are necessary for 3G terminals. Moreover, according to 3GPP/3GPP2, 3G terminals support only part of error resilience tools of H.264/AVC. This paper lists various error resilience tools and analyzes their usability in 3G environment, and at the same time, some error resilience schemes are proposed. Performances of these error resilience schemes are tested using offline common test conditions. Experiments shows that, in 3G environment, encoding with simple FMO mode and extra intra block refreshing can achieve the best error correction ability, because this method can make full use of spatial correlation for intra predication and reduce the requirement of bit rate.

H.264/AVC error resilience tools suitable for 3G mobile video services *

The emergence of third generation mobile system (3G) makes video transmission in wireless environment possible, and the latest 3GPP/3GPP2 standards require 3G terminals support H.264/AVC. Due to high packet loss rate in wireless envi- ronment, error resilience for 3G terminals is necessary. Moreover, because of the hardware restrictions, 3G mobile terminals support only part of H.264/AVC error resilience tool. This paper analyzes various error resilience tools and their functions, and presents 2 error resilience strategies for 3G mobile streaming video services and mobile conversational services. Performances of the proposed error resilience strategies were tested using off-line common test conditions. Experiments showed that the proposed error resilience strategies can yield reasonably satisfactory results.

Region of Interest Fragile Watermarking for Image Authentication

Digital watermarking plays an important role in image verification and copyright protection. A watermarking scheme for authenticating ROI (region of interest) of image has been proposed in the paper. To embed the watermark in the interior of ROI, Poisson matting technique is introduced to extract the region of interest of image. The color foreground obtained by Poisson matting is converted to the binary image as reference mask. According to principles of wavelet, we construct watermark embedding function and accurately embed watermark in the interior of ROI. Exploiting watermark extraction function, we extract the watermark from watermarked image. Differentiating the values between embedding watermark and extracted watermark can detect whether ROI of image was tampered, and where was tampered. Experiment results have demonstrated that the presented watermarking scheme can detect tamper in the interior of ROI for image authentication

Vehicles detection in Traffic Flow

Traffic Flow Analysis System is an important part of Intelligent Transportation Systems. It mainly contains two parts: vehicle detection part and vehicle tracking part. The efficient video object segmentation algorithm is the basis of vehicle detection part that aims to segment each vehicle correctly. In this paper, according to the street traffic environment, we adopt a multiple video object segmentation algorithm in vehicle detection. The algorithm consists of training section and segmentation section. At the training section, it uses codebook method to train the vehicle images: First, it uses Scale-invariant feature transform method to extract the features of vehicle image samples. Secondly, it segments the images into small patches to cluster. Third, it uses a new way to activate the codebook that can largely reduce the numbers of vehicle sample images. At the segmentation section, it uses an Implicit Shape Model to combine the recognition knowledge and the segmentation knowledge together. At last, we use this algorithm to implement a prototype of traffic flow analysis system, and achieve the expected results.

Palmprint Recognition Based on PFI and Fuzzy Logic

Palmprint is one of the most reliable features in personal identification because of its stability and uniqueness. This paper proposed a novel palmprint recognition algorithm based on principal lines: a new irregular geometrical shape was employed to get valid palmprint region, which decreased the influence of large noises; not only structure feature, but also intension information were included in the final extracted principal lines, which provides much sufficient clues for palmprint recognition; the probability feature image (PFI) was used in order to suppress random noises in feature image; features from several training samples were merged into one template, which guaranteed the integrity of feature; fuzzy logic was employed in matching algorithm. The high recognition rates obtained in the experiments show the efficiency of proposed algorithm.

Uniform color transfer

We present in this paper a general algorithm called uniform color transfer for transferring dominant colors in one image to another. Our algorithm frees users from interactions required for colorizing grayscale image or transferring color between images. Different from existing algorithms, we cluster the source color image into regions using the GMM-EM method, and the target image using the K-means algorithm. We then impose chromatic mean values on corresponding source image regions in the target image. Experiments showed that our algorithm can give better results.

H.264/SVC error resilience strategies for 3G video service

Scalable Video Codec (SVC) is an extension to the H.264/AVC that provides support for different types of scalability. 3GPP video services (e.g. Multimedia Broadcast/Multicast Services, Packet-switched Streaming Service and Conversational Service etc.) may greatly benefit from the adoption of SVC. The latest 3GPP/3GPP2 standards have already begun to support for H.264/SVC. Due to high packet loss rate in wireless environment, error resilience is still a challenge for H.264/SVC and error resilience tools of H.264/SVC are different from H.264/AVC. In this paper, we analyze the various error resilience tools of H.264/SVC and their functions and present two error resilience strategies for Multimedia Broadcast/Multicast Services and Conversational Service respectively. We test the proposed strategies by using the off-line common test conditions. Our experiments show that the proposed strategies can achieve satisfactory results.

Radius-normal histogram and hybrid strategy for 3D shape retrieval

Recent development in computer hardware and modeling technologies has led to a fast increasing of 3D models. To help user find expected models accurately and efficiently, technologies on content-based 3D model retrievals have become one of the most challenging research topic recently. In this paper, radius-normal histogram(RNH) is proposed to describe shape contents and used for shape retrievals. The RNH shape descriptor first uses a series of concentric spheres to capture the point distribution information of the given model. Then for points in each concentric sphere, a radian normal angle is computed to extract the local geometry features. Finally, the radius-normal histogram is constructed by using the extracted shape signatures. The proposed shape representation remains invariant under rotations. It can be generated from the given 3D model efficiently and easily as well. Performance comparisons for the shape benchmark database have proven that the proposed algorithm can achieve better retrieving performance than other similar histogram-based shape representations. To further improve the retrieving performance, different shape features are combined based on dynamic weight selections and a hierarchical architecture is used to speed up the matching process.