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image feature based CCD Fault Diagnosis for Automatic Alignment of High Energy Laser Beams Control System

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Image Feature based CCD Fault Diagnosis for Automatic Alignm...

image block feature vectors based on a singular-value information metric and color-texture description

第32届中国控制与决策会议

作者： Qiang Ren Hailei Ren Hang Gao Baoran An Institute of Computer Application China Academy of Engineering Physis Institute of Fluid Physics China Academy of Engineering Physis

With the development of national large-scale safety-critical facilities,countries around the world have invested huge amounts of money to build a variety of *** the high energy large-scale laser beams control system,one of the major purpose of this control system is to accurately focus hundreds of high energy laser beams on a nanoscale（mm） fusion target at the precision location and *** system has tens of thousands of control nodes,including CCD and other electronic equipment,which always play a very important role in the closed-loop control *** a CCD has a fault,it will directly influence the automatic alignment of the laser beams control *** this paper,we proposed an image feature based CCD fault diagnosis method for the high energy laser control system,we first computed the histogram and analysed the main pixel distribution of each frame,and then we detect and analyze the object contour from the ***,we designed a fault diagnosis model to classify the specific fault ***,to evaluate the performance of the proposed method,we carried out a large number of *** the qualitative and quantitative analyses of the experimental results,we verified that the CCD fault diagnosis performance of the method is effective and robust.

关键词： Large-Scale Safety-Critical Facilities High Energy Laser Beams CCD Fault Diagnosis image feature

来源： cnki会议评论

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Journal of Shanghai University(English Edition) 2007年第3期11卷 205-209页

作者：王朔中路兴苏胜君张新鹏 School of Communication and Information Engineering Shanghai University Shanghai 200072 P. R. China

In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, the block is considered informative. A total of 12 features including statistics of brightness, color components and texture measures are used to form intermediate vectors. Principal component analysis is then performed to reduce the dimension to 6 to give the final feature vectors. Relevance of the constructed feature vectors is demonstrated by experiments in which k-means clustering is used to group the vectors hence the blocks. Blocks falling into the same group show similar visual appearances.

关键词： image feature color texture content-based image retrieval (CBIR) image hashing

Comparative study on the performance of textural image features for active contour segmentation

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Science China(Life Sciences) 2012年第7期55卷 637-644页

作者： MORARU Luminita MOLDOVANU Simona Dunarea de Jos University of Galati Galati RO-800008Romania

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard devia- tion textural feature and a 5x5 kernel, our curve evolution was able to produce results close to the minimal area error rate （namely 8.88% for breast images and 10.82% for liver images）. The image resolution was evaluated using the con- trast-to-gradient method. The experiments showed promising segmentation results.

关键词： active contour model image feature area error rate

Applying Wide & Deep Learning Model for Android Malware Classification

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Computer Systems Science & Engineering 2023年第6期45卷 2741-2759页

作者： Le Duc Thuan Pham Van Huong Hoang Van Hiep Nguyen Kim Khanh Ha Noi University of Science and Technology Ha Noi100000Viet Nam Academy of Cryptography Techniques Ha Noi100000Viet Nam

Android malware has exploded in popularity in recent years,due to the platform’s dominance of the mobile *** the advancement of deep learning technology,numerous deep learning-based works have been proposed for the classification of Android *** learning technology is designed to handle a large amount of raw and continuous data,such as image content ***,it is incompatible with discrete features,i.e.,features gathered from multiple ***,if the feature set is already well-extracted and sparsely distributed,this technology is less effective than traditional machine *** the other hand,a wide learning model can expand the feature set to enhance the classification *** maximize the benefits of both methods,this study proposes combining the components of deep learning based on multi-branch CNNs(Convolutional Network Neural)with wide learning *** feature set is evaluated and dynamically partitioned according to its meaning and generalizability to subsets when used as input to the model’s wide or deep *** proposed model,partition,and feature set quality are all evaluated using the K-fold cross validation method on a composite dataset with three types of features:API,permission,and raw *** accuracy with Wide and Deep CNN(WDCNN)model is 98.64%,improved by 1.38%compared to RNN(Recurrent Neural Network)model.

关键词： Wide and deep(W&D)learning convolutional neural network image feature raw features generalized features

Fast Fractal image Encoding Using an Improved Search Scheme

维普期刊数据库评论

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维普期刊数据库

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Tsinghua Science and Technology 2007年第5期12卷 602-606页

作者：周一鸣张超张曾科 Department of Automation Tsinghua University

As fractal image encoding algorithms can yield high-resolution reconstructed images at very high compression ratio, and therefore, have a great potential for improving the efficiency of image storage and image transmission. However, the baseline fractal encoding algorithm requires a great deal of time to complete the best matching search between the range and domain blocks, which greatly limits practical applications of the algorithm. In order to solve this problem, a necessary condition of the best matching search based on an image feature is proposed in this paper. The proposed method can reduce the search space significantly and excludes the most inappropriate domain blocks for each range block before carrying out the best matching search. Experimental results show that the proposed algorithm can produce good quality reconstructed images and requires much less time than the baseline encoding algorithm. Specifically, the new algorithm can speed up encoding by about 85 times with a loss of just 3 dB in the peak signal to noise ratio （PSNR）, and yields compression ratios close to 34.

关键词： fractal image encoding image feature matching search

NEW CORNER DETECTION ALGORITHM BASED ON MULTI-feature SYNTHESIS

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Transactions of Nanjing University of Aeronautics and Astronautics 2004年第3期21卷 174-178页

作者：邱卫国昂海松南京航空航天大学航空宇航学院

Corner detection is a chief step in computer vision. A new corner detection algorithm in planar curves is proposed. Firstly, from the human perception, two key characteristics are given as an amendment of the traditional corner properties. Based on the two properties, the concept of the fuzzy set is introduced into a detection. Secondly, the extracted-formulae of three groups including the features of the corner subject degree are derived. Through synthesizing the features of three groups, the judgments of the corner detection, location, and optimization are obtained. Finally, by using the algorithm the detection results of several examples and feature curves for some interested parts, as well as the detection results for the test images history in references are given. Results show that the algorithm is easily realized after adopting the fuzzy set, and the detection effect is very ideal.

关键词： image feature corner detection fuzzy infe-rence subject degree