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International Congress on image and Signal processing

作者： Zilong He Haixun Yu School of Electronics and Information Northwestern Ploytechnical University Xi'an China

ISBN: (纸本)9781479927654

Piezoresistive pressure sensors are widely used in industrial measurement and control systems and can greatly affect the performance of these systems. However, cross-sensitivity exists in most pressure sensors, whose static characteristics are not only influenced by the variety of target parameters but also subjected to non-target parameters. In this paper, we have proposed a new method based on 1stOpt (First Optimization) to reduce cross-sensitivity and improve the stability and measuring accuracy of pressure sensors. It can be applied for the fusion of two data sets generated by pressure sensors. To demonstrate the usefulness of this method, a practical case study is investigated. Compared with two widely used methods, SVR (support vector regression) and BP neural network (back propagation neural network), data fusion based on IstOpt proves to be of higher accuracy, better robustness and wider application range.

关键词： Data fusion 1stOpt Pressure sensor

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A visualized acoustic saliency feature extraction method for environment sound signal processing

A visualized acoustic saliency feature extraction method for...

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IEEE Region 10 International Conference TENCON

作者： Jingyu Wang Ke Zhang Kurosh Madani Christophe Sabourin School of Astronautics Northwestern Polytechnical University Xi'an China Signals Images & Intelligent Systems Laboratory LiSSi - EA-3956 Univcrsite Paris-Est Creteil Paris France

ISBN: (纸本)9781479928286

Environment perception is an important research issue for both unmanned ground vehicles and robots. To improve the capacity of perception, a visualized acoustic saliency feature extraction (VASFE) method based on both the short-time Fourier transform (STFT) and the Mel-Frequency Cepstrum Coefficient (MFCC) for environment sound signal processing is proposed in this paper. Sound signal is visualized by using the STFT algorithm as local image feature and the Mel-Frequency Cepstrum Coefficient (MFCC) is used to represent the local acoustic feature of the signal. The proposed VASFE method is tested by the natural sound data which collected from real world of both indoor and outdoor environment. The results show that this method is able to extract the saliency features of both long-term and short-term sound signal successfully and clearly, and conducts to very distinguishable features for future processing of environment sound information.

关键词： Feature extraction Signal processing algorithms Spectrogram Mel frequency cepstral coefficient Equations Visualization

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Automatic recognition of radar signals based on time-frequency image character

Automatic recognition of radar signals based on time-frequen...

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IET International Radar Conference 2013

作者： Zhu, Jiandong Zhao, Yongjun Tang, Jiang Zhengzhou Information Science and Technology Institute Zhengzhou China

ISBN: (纸本)9781849196031

Radar signal recognition is one of the key technologies of modern electronic surveillance systems. Time-frequency image provides a new way for recognizing the radar signals. In this paper, a series of image processing methods containing image enhancement, image threshold binarization and mathematical morphology is utilized to extract the shape character of smoothed pseudo wigner-ville time-frequency distribution of radar signals, and then realize the identification of radar signals by the character. Simulation results of eight kinds of typical radar signals demonstrate that when signal noise ratio (SNR) is greater than -3dB, the Legendre moments shape character of the time-frequency image is very stable. Moreover, the recognition rate by the character is more than 90% except for the FRANK code signal when SNR ≥ -3dB Compared with existing algorithms, the proposed algorithm also has advantages of less character dimension and shorter computation time.

关键词： image enhancement

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面向SAR图像目标识别的鲁棒处理算法

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系统工程与电子技术 2013年第12期35卷 2489-2494页

作者：刘中杰曹云峰庄丽葵丁萌王西超南京航空航天大学自动化学院江苏南京210016 空军驻京昌地区军事代表室北京100041 南京航空航天大学航天学院江苏南京210016 南京航空航天大学民航学院江苏南京210016

现有合成孔径雷达图像的目标识别方法通常要进行预处理,预处理对于识别率影响较大。但是,针对不同的合成孔径雷达目标图像,预处理算法的自适应性很难得到保证。将基于核的主成分分析与稀疏表示相结合,只需很少的观测数据就能得到高识别... 详细信息

现有合成孔径雷达图像的目标识别方法通常要进行预处理,预处理对于识别率影响较大。但是,针对不同的合成孔径雷达目标图像,预处理算法的自适应性很难得到保证。将基于核的主成分分析与稀疏表示相结合,只需很少的观测数据就能得到高识别率的目标识别结果,节省了数据存储量和计算量。首先,阐述了压缩感知的基本理论;其次,提出了基于核主成分分析和稀疏表示的合成孔径雷达图像目标识别算法;最后,选取MSTAR数据库中的5类目标进行实验。仿真结果表明,在没有方位角预测的情况下,该算法仍能有效地识别目标,与其他识别算法相比,在同等噪声污染的图像下,具有较高的识别率。

关键词：目标识别压缩感知稀疏表示核主成分分析合成孔径雷达图像

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A WSN approach to unmanned aerial surveillance of traffic anomalies: Some challenges and potential solutions

A WSN approach to unmanned aerial surveillance of traffic an...

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East-West Design & Test Symposium (EWDTS)

作者： David Afolabi Ka Lok Man Hai-Ning Liang Eng Gee Lim Zhun Shen Chi-Un Lei Tomas Krilavičius Yue Yang Lixin Cheng Vladimir Hahanov Igor Yemelyanov Xi'an Jiaotong-Liverpool University Suzhou Jiangsu CN Xi'an Jiaotong-Liverpool University Suzhou China University of Hong Kong Hong Kong

ISBN: (纸本)9781479920976

Stationary CCTV cameras are often used to help monitor car movements and detect any anomalies-e.g., accidents, cars going faster than the allowed speed, driving under the influence of alcohol, etc. The height of the cameras can limit their effectiveness and the types of image processing algorithm which can be used. With advancements in the development of inexpensive aerial flying objects and wireless devices, these two technologies can be coupled to support enhanced surveillance. The flying objects can carry multiple cameras and be sent well above the ground to capture and feed video/image information back to a ground station. In addition, because of the height the objects can achieve, they can capture videos and images which could lend themselves more suitably for the application of a variety of video and image processing algorithms to assist analysts in detecting any anomalies. In this paper, we examine some main challenges of using flying objects for surveillance purposes and propose some potential solutions to these challenges. By doing so, we attempt to provide the basis for developing a framework to build a viable system for improved surveillance based on low-cost equipment.

关键词： Wireless sensor networks Surveillance Cameras Wireless communication Vehicles Robot sensing systems

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Range ambiguity suppression by azimuth phase coding in multichannel SAR systems

Range ambiguity suppression by azimuth phase coding in multi...

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IET International Radar Conference 2013

作者： Yang, Jun Sun, Guangcai Wu, Yufeng xing, Mengdao Key Laboratory of Radar Signal Processing XiDian University Xi'an 710071 China

ISBN: (纸本)9781849196031

Among the techniques for range ambiguity suppression, the azimuth phase coding (APC) stands out for its effectiveness for point and distributed targets with low implementation complexity. After modulation to the transmitted signal and the corresponding demodulation to the received signal, the residual modulation phase of the ambiguity signal shifts its Doppler spectrum, so that the spectrum of the useful signal and that of the ambiguity are not exactly superimposed. This enables an azimuth filter to eliminate a part of the ambiguity power. If it is desired to get an ambiguity-free SAR image, the pulse reputation frequency (PRF) should be several times larger than the Doppler bandwidth of the desired Doppler spectrum, which is hard to be satisfied in high-resolution wide-swath spaceborne SAR systems. This paper introduces a method for range ambiguity suppression based on the APC technology in multichannel SAR systems when the PRF is only a bit larger than the Doppler bandwidth. After applying the APC technique, the space-time spectrum of the ambiguity swath is separated from that of the useful signal. In multichannel SAR systems, the desired 2-D spectrum and the spectrum of the ambiguity swath can be obtained simultaneously by using the position information of antenna phase centres. Conventional imaging algorithms can then be applied to both spectrums to obtain SAR images of the imaging area and the ambiguity swaths. Simulation results confirm the effectiveness of this method.

关键词： Synthetic aperture radar

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Benchmarking asymmetric 3D-2D face recognition systems

Benchmarking asymmetric 3D-2D face recognition systems

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International Conference on Automatic Face and Gesture Recognition

作者： xi Zhao Wuming Zhang Georgios Evangelopoulos Di Huang Shishir K. Shah Yunhong Wang Ioannis A. Kakadiaris Liming Chen Computational Biomedicine Lab Department of Computer Science University of Houston Houston TX USA LIRIS Lab Ecole Centrale de Lyon France Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781467355452

Asymmetric 3D-2D face recognition (FR) aims to recognize individuals from 2D face images using textured 3D face models in the gallery (or vice versa). This new FR scenario has the potential to be readily deployable in field applications while still keeping the advantages of 3D FR solutions of being more robust to pose and lighting variations. In this paper, we propose a new experimental protocol based on the UHDB11 dataset for benchmarking 3D-2D FR algorithms. This new experimental protocol allows for the study of the performance of a 3D-2D FR solution under pose and/or lighting variations. Furthermore, we also benchmarked two state of the art 3D2D FR algorithms. One is based on the Annotated Deformable Model (using manually labeled landmarks in this paper) using manually labeled landmarks whereas the other makes use of Oriented Gradient Maps along with an automatic pose estimation through random forest.

关键词： Face Lighting Probes Pipelines Solid modeling Estimation Face recognition

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Design of Hough transform hardware accelerator for lane detection

Design of Hough transform hardware accelerator for lane dete...

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IEEE Region 10 International Conference TENCON

作者： Hyo-Kyun Jeong Yong-Jin Jeong Department of electronics and communication engineering Kwangwoon University Seoul Korea

The Hough transform is a well-known straight line detection algorithm and it has been widely used for many lane detection algorithms. However, its real-time operation is not guaranteed due to its high computational complexity. In this paper, we designed a Hough transform hardware accelerator on FPGA to process it in real time. Its FPGA logic area usage was reduced by limiting the angles of the lines to (-20, 20) degrees which are enough for lane detection applications, and its arithmetic computations were performed in parallel to speed up the processing time. As a result of FPGA synthesis using xilinx Vertex-5 XC5VLX330 device, it occupies 4,521 slices and 25.6Kbyte block memory giving performance of 10,000fps in VGA images(5000 edge points). The proposed hardware on FPGA (0.1ms) is 450 times faster than the software implementation on ARM Cortex-A9 1.4GHz (45ms). Our Hough transform hardware was verified by applying it to the newly developed LDWS (lane departure warning system).

关键词： Transforms Hardware Field programmable gate arrays image edge detection Software Real-time systems Vehicles

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Local structure divergence index for image quality assessment

Local structure divergence index for image quality assessmen...

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19th International Conference on Neural Information processing, ICONIP 2012

作者： Gao, Fei Tao, Dacheng Li, Xuelong Gao, xinbo He, Lihuo School of Electronic Engineering Xidian University Xi'an Shaanxi 710071 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney Broadway NSW 2007 Australia State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision Mechanics Xi'an Shaanxi 710119 China

ISBN: (纸本)9783642344992

image quality assessment (IQA) algorithms are important for image-processing systems. And structure information plays a significant role in the development of IQA metrics. In contrast to existing structure driven IQA algorithms that measure the structure information using the normalized image or gradient amplitudes, we present a new Local Structure Divergence (LSD) index based on the local structures contained in an image. In particular, we exploit the steering kernels to describe local structures. Afterward, we estimate the quality of a given image by calculating the symmetric Kullback-Leibler divergence (SKLD) between kernels of the reference image and the distorted image. Experimental results on the LIVE database II show that LSD performs consistently with the human perception with a high confidence, and outperforms representative structure driven IQA metrics across various distortions. © 2012 Springer-Verlag.

关键词： image quality

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Parallel program design for JPEG compression encoding

Parallel program design for JPEG compression encoding

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2012 9th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2012

作者： Liu, Duo Fan, xiao Ya School of Computer Science and Engineering Northwestern Polytechnical University Xi' an Shaanxi 710072 China

ISBN: (纸本)9781467300223

image compression is a kind of data compression technology. The aim of image compression is to reduce redundant information in image data. However, most image compression algorithms have problems such as computational complexity, computational load and so on. Parallel computing is an effective means to improve the processing speed. With the development of high-performance parallel processing systems, parallel image processing algorithms provides more space for improving image processing speed. And with the improvement of GPU performance, GPU is increasingly applied in the computing-concentrated data operation. According to the parallelism and programmability of CUDA, the acceleration for JPEG compression is addressed in this paper. CUDA makes it possible for GPU to do the general purpose computing. The powerful parallel computing power of CUDA GPU can improve the processing speed of JPEG image compression easily. For the parallel processing features and programmability of CUDA, this paper introduces a method of accelerating image compression based on CUDA. An optimal algorithm is proposed as well. The introduction of CUDA allows the image compression for nearly 20 to 24 times speedup. In the end of the paper, we optimize and test the program, and make the analysis of experimental results. Finally we summarize some hardware and software features of CUDA, and propose a basic method of optimizing CUDA kernels from the analysis of the experiment. © 2012 IEEE.

关键词： Graphics processing unit

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