Browsing by Author "Wang, SZ"

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A new motion compensation design for H.264/AVC decoder
(2005)
Wang, SZ
;
Lin, TA
;
Liu, NM
;
Lee, CY
;
電子工程學系及電子研究所
Motion compensation is always the main bottleneck in real-time or high quality video applications; thus, fast and efficient motion compensation is necessary. In this paper, a new motion compensation design is presented to overcome large calculation time of complicated motion vector prediction. (MVP) algorithm and high motion resolution in H.264/AVC. By applying 4x4 block based parallelism and context switch buffers in our design, it can efficiently reduce memory access and increase data reuse probability such that achieve real-time decoding with 1080HD (1920x1088) at 100 MHz and search range [-64,+63.75].
An H.264/AVC decoder with 4x4-block level pipeline
(2005)
Lin, TA
;
Wang, SZ
;
Liu, TM
;
Lee, CY
;
電子工程學系及電子研究所
In this paper, we propose a 4x4-block level pipelining architecture with instantaneous switching scheme and optimal decoding ordering of H.264/AVC decoder. Compared with conventional H.264/AVC video decoders [1)[2], which adopt macroblock level pipelines, our proposed 4x4-block level pipelining architecture of H.264/AVC decoder achieves better hardware utilization. Moreover, our proposed decoding ordering can effectively save memory access and reduce processing cycles, which results in 260,000 MB/s under 100MHZ clock frequency. By adopting these two techniques, our proposed design supports real time decoding with 1080HD (1920x1088) video sequence in 30fps (244,800 MB/s required) and level 4 of baseline profile.
Detection and recognition of license plate characters with different appearances.
(2003)
Wang, SZ
;
Lee, HJ
;
資訊工程學系
;
Department of Computer Science
This paper proposes an approach to developing an automatic license plate recognition system. Car images are taken from various positions outdoors. Because of the variations of angles from the camera to the car, license plates have various locations and rotation angles in an image. In the license plate detection phase, the magnitude of the vertical gradients is used to detect candidate license plate regions. These candidate regions are then evaluated based on three geometrical features: the ratio of width and height, the size and the orientation. The last feature is defined by the major axis. In the character recognition phase, we must detect character features that are non-sensitive to the rotation variations. The various rotated character images of a specific character can be normalized to the same orientation based on the major axis of the character image. The crossing counts and peripheral background area of an input character image are selected as the features for rotation-free character recognition. Experimental results show that the license plates detection method can correctly extract all license plates from 102 car images taken outdoors and the rotation-free character recognition method can achieve an accuracy rate of 98.6%.
Dual-binarization and anisotropic diffusion of Chinese characters in calligraphy documents
(2001)
Wang, SZ
;
Lee, HJ
;
資訊工程學系
;
Department of Computer Science
In this paper, we propose a method for calligraphy document binarization. First, the properties of calligraphy documents are analyzed to classify calligraphy documents into two classes: tablet documents and writing documents. Because calligraphy documents have serious noises and large variations in gray scales of the characters, the foreground will be broken after thresholding. The anisotropic diffusion technique is used to smooth input calligraphy documents, which can preserve character boundaries well. Last, noises are removed from binarized images based on the information of stroke widths. In our experiments, 90 tablet documents and 51 writing documents are binarized and well binarized results are obtained.
Extraction and recognition of license plates of motorcycles and vehicles on highways
(2004)
Lee, HJ
;
Chen, SY
;
Wang, SZ
;
資訊工程學系
;
Department of Computer Science
In this paper, a recognition system is proposed to extract and recognize license plates of motorcycles and vehicles on highways. In the first stage, a block-difference method is used to detect moving objects. According to the variance and the similarity of the MxN blocks defined on two diagonal lines, the blocks are categorized as three kinds: low-contrast, stationary and moving blocks. In the second stage, a screening method based on the projection of edge magnitudes is used to find two peaks in the projection histograms to bound license plates. The scanning lines with low counts can be removed. In the third stage, character images are segmented and recognized. In our experiments, we tested 180 pairs of images. The block-difference method has a 98% success rate and can remove 88% of pixels from an image on average. The screening method has a 94.4% success rate and the character recognition method has a 95.7% precision rate.