Yung-Sheng Chen

Morphology-based license plate detection from complex scenes

This paper presents a morphology-based method for detecting license plates from cluttered images. The proposed system consists of three major components. At the first, a morphology-based method is proposed to extract important contrast features as guides to search the desired license plates. The contrast feature is robust to lighting changes and invariant to several transformations like scaling, translation, and skewing. Then, a recovery algorithm is applied for reconstructing a license plate if the plate is fragmented into several parts. The last step is to do license plate verification. The morphology based method can significantly reduce the number of candidates extracted from the cluttered images and thus speeds up the subsequent plate recognition. Under the experimental database, 128 examples got from 130 images were successfully detected. The average accuracy of license plate detection is 98%. Experimental results show that the proposed method improves the state-of-the-art work in terms of effectiveness and robustness of license plate detection.

Shadow elimination for effective moving object detection by Gaussian shadow modeling

Abstract This paper presents a novel approach for eliminating unexpected shadows from multiple pedestrians from a static and textured background using Gaussian shadow modeling. First, a set of moving regions are segmented from the static background using a background subtraction technique. The extracted moving region may contain multiple shadows from various pedestrians. In order to remove these unwanted shadows completely, a histogram-based method is proposed for isolating each pedestrian from the extracted moving region. Based on the results, a coarse-to-fine shadow modeling process is then applied for eliminating the unwanted shadow from the detected pedestrian. At the coarse stage, a moment-based method is first used for obtaining the rough shadow boundaries. Then, the rough approximation of the shadow region can be further refined through Gaussian shadow modeling. The chosen shadow model is parameterized with several features including the orientation, mean intensity, and center position of a shadow region. With these features, the chosen model can precisely model different shadows at different conditions and provide good capabilities for completely eliminating the unexpected shadows from the scene background. Due to the simplicity of the proposed method, all the shadows can be eliminated immediately (in less than 0.5 s). Experiments demonstrate that approximately 94% of shadows can be successfully eliminated from the scene background.

A modified fast parallel algorithm for thinning digital patterns

Abstract A modified version of the fast parallel thinning algorithm proposed by Zhang and Suen is presented in this paper. It preserves the original merits such as the contour noise immunity and good effect in thinning crossing lines; and overcomes the original demerits such as the serious shrinking and line connectivity problems.

Motion-based video retrieval by trajectory matching

This paper proposes a hybrid motion-based video retrieval system to retrieve desired videos from video databases through trajectory matching. The hybrid method includes a sketch-based scheme and a string-based one to analyze and index a trajectory with more syntactic meanings. First of all, this method uses a sampling technique to extract a set of control points from each trajectory as features. Then, the sketch-based method uses a curve fitting technique to interpolate some missed data in this set of control points. Then, the visual distance between any two trajectories can be directly measured by comparing their position data. The visual distance is good in solving the problem of translation-invariant trajectory matching but poor in solving the problem of partial trajectory matching. Therefore, in addition to the visual distance, the hybrid method uses the string-based scheme to compare any two trajectories according to their syntactic meanings. With the help of the syntactic distance, many impossible candidates can be filtered out in advance and thus the accuracy of video retrieval can be much enhanced. In addition, the problem of partial trajectory matching will become easy to be solved. Thus, even though a partial trajectory is queried, all desired video clips still can be very accurately retrieved. Experimental results have proved the superiority of our proposed method.

An Enhanced ZigBee Indoor Positioning System With an Ensemble Approach

This paper presents a framework for ZigBee indoor positioning with an ensemble approach. This approach exploits the complementary advantages of various algorithms, weights the estimation results, and combines them to improve accuracy. This is achieved by dynamically analyzing the diverse patterns of inputs and combining base positioning algorithms with spatial dependent weights. The experiments were conducted in a realistic ZigBee sensor network. Results demonstrated that the proposed approach apparently achieves more accurate location estimation than the compared methods including the gradient-based search, linear squares approximation, multidimensional scaling, fingerprinting method, and a multi-expert system.

Accurate optical flow computation under non-uniform brightness variations

In this paper, we present a very accurate algorithm for computing optical flow with non-uniform brightness variations. The proposed algorithm is based on a generalized dynamic image model (GDIM) in conjunction with a regularization framework to cope with the problem of non-uniform brightness variations. To alleviate flow constraint errors due to image aliasing and noise, we employ a reweighted least-squares method to suppress unreliable flow constraints, thus leading to robust estimation of optical flow. In addition, a dynamic smoothness adjustment scheme is proposed to efficiently suppress the smoothness constraint in the vicinity of the motion and brightness variation discontinuities, thereby preserving motion boundaries. We also employ a constraint refinement scheme, which aims at reducing the approximation errors in the first-order differential flow equation, to refine the optical flow estimation especially for large image motions. To efficiently minimize the resulting energy function for optical flow computation, we utilize an incomplete Cholesky preconditioned conjugate gradient algorithm to solve the large linear system. Experimental results on some synthetic and real image sequences show that the proposed algorithm compares favorably to most existing techniques reported in literature in terms of accuracy in optical flow computation with 100% density.

Adaptive thresholding algorithm and its hardware implementation

Abstract This paper presents an adaptive raster-scan thresholding algorithm which can deal with an image acquired under imperfect illumination. A statistical measurement called LSSD (Largest Static State Difference) relating to the gray-level variation is found first. According to the measurement, the pixels are separated into static and transient states which are treated by two different procedures, respectively. A hardware implementation of this algorithm shows that the real-time requirement can be met. Experiments of applying this algorithm to extracting characters from documents confirmed that a reasonable binary image can be efficiently and effectively obtained from a gray-level image under various illuminations.

A systematic approach for designing 2-subcycle and pseudo 1-subcycle parallel thinning algorithms

Abstract This paper describes a systematic approach for designing parallel thinning algorithms, in which three new functions, named local connecting, extended local connecting and erosive direction number, are introduced. With these functions as well as two properties of shape invariance of local edges and local straight lines, all the possible cases of 2-subcycle parallel thinning algorithm are constructed and all the corresponding removing conditions are generated and assigned automatically. In addition, the pseudo 1-subcycle parallel thinning algorithm is also presented. Finally, the effects and efficiency of the above proposed algorithms are analyzed and compared with those of some presently well-known algorithms. Experimental results confirm this new approach, and an efficient and effective algorithm has been built for practical applications.

Measuring of a three-dimensional surface by use of a spatial distance computation

The correspondence problem of two captured images, which are obtained by projecting a structured light on the measuring surface, are explored for when three-dimensional information of a given surface is needed. In our system the constraint that codifies the pattern projected on the surface has been simplified by using a random speckle pattern, thus the correspondence problem is reduced tolocal matching between two captured images and solved by a spatial distance computation technique. The performance of our approach, which includes a disparity error analysis, a search range suggestion, and a disparity gradient limit, are investigated and discussed. Some parameters, such as percentile constraint, sampling interval, and subpixel compensation proper for use in this approach are suggested. Experiments have shown the feasibility of the proposed method.

A shadow elimination method for vehicle analysis

This paper proposes a novel shadow elimination method for solving the shadow occlusion problems of vehicle analysis. Different from traditional methods which only consider intensity properties in shadow modeling, this method introduces a new important feature to eliminate all unwanted shadows, i.e., lane line geometries. In this approach, a set of moving vehicles are first segmented from backgrounds by using a background subtraction technique. At this moment, each extracted vehicle may contain shadows which cause the failure of further vehicle analysis. To remove these unwanted shadows, a histogram-based method is then proposed for detecting different lane dividing lines from video sequence. According to these lines, a line-based shadow modeling process is then applied for shadow elimination. Two kinds of lines are used here for shadow elimination, i.e., the ones parallel and vertical to lane directions, respectively. Different type of lines has different capabilities to eliminate different kinds of shadows. Experiments demonstrate that approximately 92% of shadows can be successfully eliminated from moving vehicles.