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	1. Pedestrian Detection by Boosting Neural Networks
	Jia Hui-Xing,Zhang Yu-Jin
	Electrics, Communication and Autocontrol Technology 17 December 2008
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	Abstract:In this paper, a fast pedestrian detection system by boosting neural network classifiers is built. The object to be detected is represented by a collection of blocks. For each block, the histogram of orientated gradients feature is extracted and a neural network classifier is built as weak hypothesis. Then these hypotheses are selected sequentially by Gentle Adaboost, and the cascade structure is used to speedup the detector. Compared to global linear SVM classifiers, the new method gets better performance on the INRIA pedestrian detection database at a much faster speed.
	TO cite this article:Jia Hui-Xing,Zhang Yu-Jin. Pedestrian Detection by Boosting Neural Networks[OL].[17 December 2008] http://en.paper.edu.cn/en_releasepaper/content/26680


	2. Super-resolution algorithm based on local gradient
	Jinyu Chu,Ju Liu,Jianping Qiao,Xiaoling Wang
	Electrics, Communication and Autocontrol Technology 19 June 2008
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	Abstract:This paper presents a super-resolution method based on gradient-based adaptive interpolation. In this method, in addition to considering the distance between the interpolated pixel and the neighboring valid pixel, the interpolation coefficients take the local gradient of the original image into account. The smaller the local gradient of a pixel is, the more influence it should have on the interpolated pixel. And wiener filter is finally applied to reduce the blurring and noise of the interpolated high resolution image. Experimental results show that our proposed method not only substantially improves the subjective and objective quality of restored images, especially enhances edges, but also is robust to the registration error and has low computational complexity.
	TO cite this article:Jinyu Chu,Ju Liu,Jianping Qiao, et al. Super-resolution algorithm based on local gradient[OL].[19 June 2008] http://en.paper.edu.cn/en_releasepaper/content/22375

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	3. An Improved Face Hallucination Based PCA
	Xiaoling Wang,Ju Liu,Jianping Qiao,Jinyu Chu
	Electrics, Communication and Autocontrol Technology 21 April 2008
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	Abstract:In this paper, based on Circularly Symmetrical Gabor Transform (CSGT) and Principal Component Analysis (PCA), we propose a face hallucination approach. In this approach, all of the face images (both input face image and original training database) are transformed through CSGT at first and then local extremes criteria is utilized to extract the intrinsic features of the faces. Based on these features, we calculate Euclidean distances between the input face image and every image in the original training database, and then Euclidean distances are used as criteria to choose the reasonable training database. Once the training database is chosen, we use PCA to hallucinate the input face image as the linear combination of the chosen training images. Experimental results show that our approach can choose training database automatically according to the input face image and get high quality super-resolution image.
	TO cite this article:Xiaoling Wang,Ju Liu,Jianping Qiao, et al. An Improved Face Hallucination Based PCA[OL].[21 April 2008] http://en.paper.edu.cn/en_releasepaper/content/20681


	4. Image Deringing with Adaptive Bilateral Filter
	Guangtao Zhai,Yi Xu,Xiaokang Yang,Wenjun Zhang,Songyu Yu
	Electrics, Communication and Autocontrol Technology 02 April 2008
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	Abstract:In this paper, we tailor the bilateral filter towards the task of suppressing the ringing artifact commonly occurred on JPEG2000 images under low bitrates. The proposed adaptive bilateral filter varies from its original form as the pixel moves from a monotone area towards an edge one. Also the local spreads of the domain and range filters are tuned with the extent of texture activity. The edge detection and distance transform are used to indicate the local edge and texture activity indexes. Experimental results show that the adaptive bilateral filter can effectively smooth out the annoying ringing artifact and ameliorate the visual quality.
	TO cite this article:Guangtao Zhai,Yi Xu,Xiaokang Yang, et al. Image Deringing with Adaptive Bilateral Filter[OL].[ 2 April 2008] http://en.paper.edu.cn/en_releasepaper/content/20051


	5. Unified Artifacts Reduction for Block DCT Compressed Images
	Guangtao Zhai,Yi Xu,Xiaokang Yang,Wenjun Zhang,Songyu Yu
	Electrics, Communication and Autocontrol Technology 02 April 2008
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	Abstract:We propose a unified scheme to alleviate the blocking, ringing and blurring artifacts in block DCT compressed images. The image is decomposed into 2 levels using the over-complete wavelet transform, and the wavelet coefficients are filtered with consideration of local image properties. For the smooth region, the wavelet coefficients are averaged over the range of blocking artifacts’ extension in the over-complete wavelet transform domain on respective levels. For the texture region, only the coefficients on the first level are averaged to prevent over-smooth of the image. And for the edge region, the coefficients are first smoothed and then high-pass filtered to enhance the edges so as to restrain the ringing and blurring artifacts. The inverse transform of the filtered coefficients is performed towards the quality enhanced image. And a quantization constraint is imposed on the final result for better PSNR and visual performance.
	TO cite this article:Guangtao Zhai,Yi Xu,Xiaokang Yang, et al. Unified Artifacts Reduction for Block DCT Compressed Images[OL].[ 2 April 2008] http://en.paper.edu.cn/en_releasepaper/content/20036


	6. Iterative Association Model for Image Annotation
	Xu Feng,Zhang YuJin
	Electrics, Communication and Autocontrol Technology 10 August 2007
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	Abstract:Information retrieval based on multi-modal data is a challenging research topic. In this paper, we propose a novel approach to associate images and text keywords, which enables automatic image annotation and keyword-based image retrieval. First, the two independent spaces, containing images and text keywords respectively, are related to each other by the parallel projection. Second, the heterogeneous link between multi-modal data is defined as the form of dot product. Consequently, the link between a new data instance and the known data in the other modality can be deduced from the two homogeneous kernels. Finally, an iterative model is proposed to optimize the link and achieve the probability association matrix between the two-modal data. According to the link from images to text keywords, the annotations for images can be achieved; according to the link from text keywords to images, images can be retrieved based on text keywords. Moreover, the proposed approach explores the relationship between multi-modal data in an unsupervised manner. We provide experimental results on the tasks of automatic image annotation and keyword-based image retrieval to show the efficacy of our approach.
	TO cite this article:Xu Feng,Zhang YuJin. Iterative Association Model for Image Annotation[OL].[10 August 2007] http://en.paper.edu.cn/en_releasepaper/content/14513


	7. Scene Categorization Based on Atmosphere Semantics
	Feng Xu,Yu-Jin Zhang
	Electrics, Communication and Autocontrol Technology 10 August 2007
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	Abstract:Image categorization and annotation with abstract semantics beyond cognitive semantic level is a difficult problem in image understanding. On the other hand, atmospheres semantics of film frames is important to convey the message behind the story. For this abstract attribute, contextual information and domain knowledge besides the traditional content features are more helpful. The domain knowledge is included by the semantic ontology and network structures learnt from data. The contextual information includes film topic, recording time, and audience response. Based on all the metadata, Bayesian networks are employed to fuse metadata and a causal strength is proposed to account for the causation. Finally, we provide extensive experimental results to demonstrate the efficacy of the proposed approach.
	TO cite this article:Feng Xu,Yu-Jin Zhang. Scene Categorization Based on Atmosphere Semantics[OL].[10 August 2007] http://en.paper.edu.cn/en_releasepaper/content/14507


	8. Study Of Adaptive Lane Detection algorithm
	Huang Tao,Liao Li
	Electrics, Communication and Autocontrol Technology 18 May 2007
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	Abstract:This paper presents a Adaptive Lane Detection algorithm .The algorithm based on geometrical transform and Hough transfer and use the least squares analysis to enhance the quality of lane detection. The algorithm have the advantages of high speed and robust. The experience proved that the algorithm is efficient and feasible.
	TO cite this article:Huang Tao,Liao Li. Study Of Adaptive Lane Detection algorithm[OL].[18 May 2007] http://en.paper.edu.cn/en_releasepaper/content/12905


	9. The Registration of INSAR Complex Images
	Peng Shurong ,Wang Yaonan ,Liu Guocai ,Wenzhong Yang
	Electrics, Communication and Autocontrol Technology 30 November 2006
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	Abstract:Registration accuracy of InSAR is a key index in the procedure of the processing InSAR data. To obtain better measuring results, A multi-steps matching method is proposed to improve registration accuracy progressively for InSAR complex image. Firstly calculate the approximate offsets by using software EnView. Then perform pixel level’s primary matching and sub-pixel level’s precise registration. The primary matching algorithm based on texture structure information. Considering that the presented algorithms are based on the amplitude map and ignore the integration, the algorithm by using global relaxation matching on account of the phase is proposed in the last matching step to reduce the matching errors and improve matching precision. The experiment verified the nicer validity of this algorithm.
	TO cite this article:Peng Shurong ,Wang Yaonan ,Liu Guocai , et al. The Registration of INSAR Complex Images[OL].[30 November 2006] http://en.paper.edu.cn/en_releasepaper/content/10091


	10. Uncoupled Fuzzy-based Geodesic Active Regions Models for Image Segmentation
	Li Canfei,Wang Yaonan
	Electrics, Communication and Autocontrol Technology 30 November 2006
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	Abstract:In this paper we present a novel Uncoupled Fuzzy-based Geodesic Active Regions (UFGAR) framework for dealing with frame partition problems in image segmentation. Like the usually Geodesic Active Regions (GAR) framework presented by N. Paragios and R. Derichhave, our framework unifies boundary and region-based information. The boundary information of the mixture model is determined using a edge detector based on the fuzzy membership functions, and the region information indicates the region intensity properties is estimated by a measure based on the fuzzy membership functions too. The defined objective function is minimized using a gradient descent method where a level set approach is used to implement the resulting PDE system. But unlike GAR, which is based on the Maximum Likelihood Principle for the observed density function image histogram using a mixture of Gaussian elements, our model is based on FCM and fuzzy membership functions. We define a novel region measure based on fuzzy membership functions to measure the property of regions. According to the motion equation, the initial curve is propagated toward the segmentation result under the influence of boundary and region-based segmentation forces, and being constrained by a regularity force. The performance of this method is demonstrated by a synthetic image, and the results of its application to brain images are presented.
	TO cite this article:Li Canfei,Wang Yaonan. Uncoupled Fuzzy-based Geodesic Active Regions Models for Image Segmentation[OL].[30 November 2006] http://en.paper.edu.cn/en_releasepaper/content/10066

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