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Research for detection level and production sales management of raisins based on NN and SAS/GIS

Advance Journal of Food Science and Technology 2013年第8期5卷 1055-1058页

作者： Xiaoling, Li Jimin, Yuan School of Computer Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent information Processing University Chengdu Chengdu 610106 China School of Computer Science and Technology Panzhihua University Pan Zhihua 610106 China

Raisins grade identification in China still relies on photoelectric sorting and manual separation, also, the function of management system for the production, processing, and sales of raisin is traditional and simple. This study presents a processing method on the basis of the Neural Network (NN) and image manipulation. Calculating the length of the long-short-axis, marking the location of it and calculated the 7 parameters, chroma, length, width and etc, and using boundary tracking algorithm, A BP NN was to build and identify the level of raisins through analysis of the external characteristics of raisins. The result of experiment indicates that average recognition rate is higher than 92%. This study took regional economy statistics of Pan Zhihua as an example, designed an system based on regional economy statistic and achieves the analytic function of regional economic statistics by utilizing distributed SAS /GIS to release the data, provide browsing, searching and analytic function of the space data for the users and accomplish data share. Therefore, the method has a great practical value, which can be applied to other. © Maxwell Scientific Organization, 2013.

关键词： processing

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A new method for ship classification and recognition

A new method for ship classification and recognition

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MIPPR 2005: Image Analysis Techniques

作者： Zhao, Guangzhou Wang, Fei Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Key Laboratory for Image Processing and Intelligent Control Wuhan 430074 China

This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.

关键词： Classification (of information)

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Second order morphology algorithm for IR small target enhancement in sea clutter background

Second order morphology algorithm for IR small target enhanc...

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2010 International Conference on Optics, Photonics and Energy Engineering, OPEE 2010

作者： Xiao, Zhou Xingang, Mou Guilin, Zhang Natl. Key Laboratory of Science and Technology on Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424452354

The framework of a second order morphology algorithm is proposed to enhance the dim small infrared target in sea clutter background with strong detector noise. First, a morphological filters bank is given. Each filter in the bank is designed to suppress its corresponding type texture. The second order process can be accomplished in two steps. The original infrared image is first filtered using each filter separately, and then the first order result is obtained by the combination of the filtered result images. The other step is essentially the same as the first one except the combination manner of the filtered result images. Second, the traditional SNR gain based evaluation of different small target enhancement algorithms is examined and a more reasonable method based on the distance between the target and the maximal background (DTMB) is described in this paper. Third, using the new evaluation method, the comparison is given by experiment through a sequence of infrared images with a dim small target. Experimental results demonstrate that the new proposed algorithm performs better in sea clutter background with strong detector noise than the traditional ones. © 2010 IEEE.

关键词： Morphology

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Robust visual tracking based on online learning of joint sparse dictionary

Robust visual tracking based on online learning of joint spa...

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6th International Conference on Machine Vision, ICMV 2013

作者： Li, Qiaozhe Qiao, Yu Yang, Jie Bai, Li Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China School of Computer Science University of Nottingham Nottingham United Kingdom

ISBN: (纸本)9780819499967

In this paper, we propose a robust visual tracking algorithm based on online learning of a joint sparse dictionary. The joint sparse dictionary consists of positive and negative sub-dictionaries, which model foreground and background objects respectively. An online dictionary learning method is developed to update the joint sparse dictionary by selecting both positive and negative bases from bags of positive and negative image patches/templates during tracking. A linear classifier is trained with sparse coefficients of image patches in the current frame, which are calculated using the joint sparse dictionary. This classifier is then used to locate the target in the next frame. Experimental results show that our tracking method is robust against object variation, occlusion and illumination change. © 2013 SPIE.

关键词： E-learning

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On realization of visualization system for global ocean simulation

On realization of visualization system for global ocean simu...

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International Conference on Audio, Language and Image processing

作者： Ming, De-Lie Gao, Peng-Fei Wang, Mi State Key Laboratory for Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei Province 430074 China

ISBN: (纸本)9781424458653

Simulating and rendering realistic ocean is always one of the most popular and difficult tasks in computer graphics and oceanography. However, because of the restriction of computer software and hardware conditions, mass data and real-time, there are less people to research global ocean simulation. Under the background of global environment simulation, the paper describes a solution for the application of global ocean simulation on the basis of previous work, and realizes the visualization system successfully using OSG (OpenSceneGraph) API and all kinds of open-source libraries, and demonstrates the result of cross-sea flight. At last, we analysis the deficiencies of our solution and make some improvement suggestions. ©2010 IEEE.

关键词： Computer hardware

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An effective document image deblurring algorithm

An effective document image deblurring algorithm

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作者： Chen, Xiaogang He, Xiangjian Yang, Jie Wu, Qiang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Centre for Innovation in IT Services and Applications University of Technology Sydney Australia Key Laboratory of System Control and Information Processing Ministry of Education China

ISBN: (纸本)9781457703942

Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method. © 2011 IEEE.

关键词： Image enhancement

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Research on large-scale scene infrared simulation based on image classification

Research on large-scale scene infrared simulation based on i...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zou, Lamei Zhang, Tianxu Lv, Wei Ao, Guoqing Institute for Pattern Recognition and Artificial Intelligence Natl. Key Laboratory of Science and Technology on Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424494040

Vega has been widely used in Virtual Reality (VR) field. Vega infrared (IR) module can implement IR simulation, but Vega IR imaging simulation's general approach does not apply to large-scale scene's infrared simulation problem. This article deeps into large-scale scene IR image simulation through Vega infrared module based on visible image, the scene's corresponding Digital Elevation Model (DEM) data and targets' 3D model. A real time large-scale IR simulation system is successfully designed and realized in this paper. At the aspect of image classification, a coarse to fine k-means clustering method based on the consistency of image color is proposed. The proposed automatic texture material mapping method based on the development of Vega TMM tool provides a fast and convenient way for large-scale scene's IR simulation based on Vega IR module. And finally, results of the large-scale scene infrared simulation show the effectiveness of this method. ©2011 IEEE.

关键词： Image classification

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Smart hyperspectral imaging detection based on electrically tunable liquid-crystal Fabry-Perot microstructure array

Smart hyperspectral imaging detection based on electrically ...

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Imaging Spectrometry XIV

作者： Liu, Kan Li, Dehua Li, Hui Zhang, Xinyu Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multispectral Information Processing Technology Wuhan 430074 Hubei China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9780819477477

A smart spectral imaging detection method based on the integration of electrically tunable liquid-crystal(LC) Fabry-Perot(FP) microstructure array is proposed. It has very broad application in many fields with advantages of low cost, highly compact integration and working without mechanical part. The device can get hundreds of spectral bands simultaneously in one frame of picture in theory. This paper proposes the structure of smart spectral imaging array device, and analyses some key issues of liquid crystal Fabry-Perot structures for imaging application and calibration. Prototypes of 4 × 4 LC-FP array with the cavity thickness ranging from 4 to 20 μm for the working wavelength in the range of 800~900nm, are made by lithography and wet etching. Test is carried out and analysed. © 2009 SPIE.

关键词： Liquid crystals

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An FPGA-based histogram equalization implementation

An FPGA-based histogram equalization implementation

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Li, Yang Zhong, Sheng Wang, Bo Yan, Luxin Liu, Tao Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China National Key Laboratory of Multi-spectral Information Processing Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Image histogram equalization technology is always a very important basic processing technology in image process field. In infrared image processing system, low contrast and shortage of gray levels often make it very difficult to observe and recognize targets. In this situation, Real-time image histogram equalization technology is often used to enhance infrared image contrast, improve infrared image quality and ameliorate image processing system performance. In embedded system, when real-time image histogram equalization is required, it is very difficult for the typical design methods by using general purpose DSP or MCU to meet the real-time requirement. It is a very good choice to choose FPGA hardware logic to implement image histogram equalization. Here in this paper, we introduce an FPGA based image histogram equalization implementation in detail which can meet real-time requirement very well. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Image enhancement

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A framework of passive millimeter-wave imaging simulation for typical ground scenes

A framework of passive millimeter-wave imaging simulation fo...

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MIPPR 2009 - Multispectral Image Acquisition and processing: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Yan, Luxin Ge, Rui Zhong, Sheng Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China National Key Laboratory of Multi-spectral Information Processing Technology Wuhan 430074 China

ISBN: (纸本)9780819478054

Passive millimeter-wave (PMMW) imaging offers advantages over visible and IR imaging in having better all weather performance. However the PMMW imaging sensors are state-of-the-art to date, sometimes it is required to predict and evaluate the performance of a PMMW sensor under a variety of weather, terrain and sensor operational conditions. The PMMW scene simulation is an efficient way. This paper proposes a framework of the PMMW simulation for ground scenes. Commercial scene modeling software, Multigen and Vega, are used to generate the multi-viewpoint and multi-scale description for natural ground scenes with visible images. The background and objects in the scene are classified based on perceptive color clusters and mapped with different materials. Further, the radiometric temperature images of the scene are calculated according to millimeter wave phenomenology: atmospheric propagation and emission including sky temperature, weather conditions, and physical temperature. Finally, the simulated output PMMW images are generated by applying the sensor characteristics such as the aperture size, data sample scheme and system noise. Tentative results show the simulation framework can provide reasonable scene's PMMW image with high fidelity. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Infrared imaging

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