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4th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)

作者： Zhang, Yunfei Lu, Bo Su, Limin Beijing Union Univ Coll Informat Being Peoples R China

ISBN: (纸本)9780769547213

This paper takes EAN-13 barcode as an example to introduce multiform algorithms about automatic recognition. The algorithms consist of sift algorithm and the algorithm of optimized similar border distance measurement. Respective experimented on the same barcode, we got the result about the two algorithms. We acquired their characteristics and the fields which they are suited in. By experiment, all of them have high rate of recognition, low requirement for images and high calculating speed. So, they can meet the needs of responsiveness and automation well.

关键词： barcode sift algorithm similar border image matching

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Copyright Protection Method based on the Main Feature of Digital Images 12th

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12th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP)

作者： Wang, Xinyi Yang, Zhenghong Niu, Shaozhang China Agr Univ Sch Sci Beijing Peoples R China Beijing Univ Posts & Telecommun Beijing Key Lab Intelligent Telecommun Software & Beijing Peoples R China

ISBN: (纸本)9783319502090;9783319502083

With the rapid development of information technology, images can be easily copied, modified, and re-released. This paper proposes a copyright protection method based on the main feature of digital images by using sift algorithm. It aims to prevent the image which main feature information is stored in database from being abused. The innovation point is to store feature information instead of images with much redundant information, which can accelerate matching. It can be judged whether a picture infringes copyright by extracting its main feature information, then comparing with those in database. The experiment results show that this method can resist tampering attack such as JPEG compression, noise, and geometric distortion.

关键词： digital image copyright protection sift algorithm main feature information image tampering search matching

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3D scene reconstruction system with hand-held stereo cameras

3D scene reconstruction system with hand-held stereo cameras

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1st International Conference on 3DTV

作者： Yun, Sang Un Min, Dongbo Sohn, Kwanghoon Yonsei Univ Dept Elect & Elect Engn Seoul 120749 South Korea

ISBN: (纸本)9781424407217

3D scene modeling is a challenging problem and has been one of the most important research topic for many years. In this paper, we describe the 3D scene reconstruction system that creates 3D models with multiple stereo image pairs acquired by hand-held device. Our algorithm consists of the following two steps, which is depth reconstruction and model registration. In the first part, we obtain the depth map with stereo matching and camera geometry in each view. The algorithm is based on adaptive window methods in hierarchical frameworks. In the second part, we use sift feature to estimate the camera motion. LMedS algorithm reduces the effect of outliers in this process. Experimental results show that the proposed algorithm provides accurate disparity map in various types of images, and the 3D model of real world's scene.

关键词： disparity estimation sift algorithm robust estimation scene reconstruction

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Power Line Fault Identification Based on Artificial Intelligence Technology 3

Power Line Fault Identification Based on Artificial Intellig...

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3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

作者： Xia, Lingzhi Zhen, Chao Cheng, Yang Liu, Yushun Li, Senlin State Grid Anhui Electric Power Co. Ltd. Electric Power Research Institute Hefei230000 China State Grid Anhui Electric Power Co. Ltd. Hefei230000 China

ISBN: (纸本)9798350318180

This research proposes a new approach to power line fault identification using artificial intelligence technology, aimed at improving accuracy and reducing identification time. The method involves constructing a scale space and detecting extreme points using the sift algorithm for precise location of the fault area. An improved version of the Grey Wolf algorithm is then used, and iterative calculation is carried out based on fitness calculation results to complete the fault identification. Experimental results demonstrate significant improvement in accuracy and reduction in identification time compared to traditional methods. © 2023 IEEE.

关键词： Artificial intelligence Fault identification Power lines sift algorithm

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The reconstruction for Han Dynasty stone images based on three-dimensional vision

The reconstruction for Han Dynasty stone images based on thr...

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International Conference on Mechatronics Engineering and Computing Technology (ICMECT)

作者： Pan Guangdong Linyi Univ Yishui 276400 Shandong Peoples R China

ISBN: (纸本)9783038351153

Mainly studying the three-dimensional reconstruction for multiple Han Dynasty stone images, this paper proposes a 3D reconstruction algorithm based on two images. The author analyzes the basic principle of sift matching points detection according to Epipolar geometry constraints and projective transformation of images in 2D plane, and establishes mathematical model for the 3D reconstruction on foundation of sequence images. The feasibility of 3D reconstruction based on the sequence images is approved by simulation for three gray-scale Han Dynasty stone digital images which provides a new research way for identifying the feature of a target by the camera.

关键词： 3D reconstruction sift algorithm Han Dynasty stone images

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Image Recognition algorithm of UAV Inspection under Machine Vision 2

Image Recognition Algorithm of UAV Inspection under Machine ...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Hu, Chenlu Mo, Zirui Zhang, Zhonghuizi Qiu, Xincheng Shihezi University School of Mechanical and Electrical Engineering Shihezi China University of Manchester School of Engineering Manchester United Kingdom

ISBN: (纸本)9798350317558

UAVs have the advantages of efficient and automated inspection in life, and have important application value in industry, construction, energy and other fields. In this paper, an improved image recognition algorithm based on machine vision is proposed to solve the problems existing in UAV inspection. Through the use of computer vision technology, this paper analyzes and processes the images captured by unmanned aerial vehicles to complete the automatic recognition and defect detection of objects. A complete algorithm system composed of image preprocessing, feature extraction, object classification, and defect recognition is also proposed. Using large-scale drone patrol image data, the method is evaluated from three aspects: accuracy, F1 value and recognition speed. After testing, the prediction accuracy of this method can reach 89% to 96%. The algorithm has made significant improvements in target recognition and defect detection. The improvement in accuracy and F1 score indicates that the algorithm can identify the target. © 2024 IEEE.

关键词： Drone Inspection Image Recognition Machine Vision sift algorithm

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Remote Sensing Image Registration Using sift and Vegetation Index Analysis

Remote Sensing Image Registration Using SIFT and Vegetation ...

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International Congress on Image and Signal Processing

作者： Buyun Lv Liaoying Zhao Xiaorun Li Inst. of Comput. Applic. Hangzhou Dianzi Univ. Hangzhou China

ISBN: (纸本)9781479958368

Aiming at the high accuracy and speed requirements of images registration for multiband data or hyperspectral data, a new method which combines scale invariant feature transform (sift) with vegetation index analysis is put forward. Firstly, feature points extracted by sift algorithm are classified into two sets -points on vegetation area and points on non-vegetation area, which is based on vegetation index;then the two sets of feature points are matched separately using spectral angle distance as the similarity measure. Transformation parameters are obtained by least square method after mismatched points are removed. Experimental results show that the proposed method achieves higher speed as well as good registration accuracy.

关键词： geophysical image processing hyperspectral imaging image matching image registration least squares approximations vegetation vegetation mapping feature points hyperspectral data least square method multiband data nonvegetation area remote sensing image registration accuracy scale invariant feature transform algorithm similarity measure spectral angle distance transformation parameters vegetation index analysis Accuracy algorithm design and analysis Feature extraction Image registration Indexes Remote sensing Vegetation mapping sift algorithm vegetation index

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Research on power equipment recognition method based on image processing

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EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING 2019年第1期2019卷 1页

作者： Wang, Haiyan Meng, Fanwei Changchun Sci Tech Univ Changchun Jilin Peoples R China

Electric energy is an indispensable energy in life, and the power network is the basis to ensure its normal circulation, in which the operation status of power equipment is one of the key factors to determine the safe and stable operation of the power network. In the information age, the traditional manual periodic inspection and the existing method of relying on manual monitoring equipment operation status can no longer meet the needs of safe operation of equipment;relying on computer technology and image recognition technology to achieve automatic identification of power equipment has become a research hot spot. In order to realize automatic identification of power equipment, this paper presents a method of recognition of power equipment based on image processing. Firstly, the power equipment image is preprocessed by various denoising and sharpening algorithms to remove the noise and distortion of the image and improve the image quality;secondly, the sift algorithm is used to extract image features, and PCA algorithm is used to reduce the dimension;finally, the support vector machine is used to classify and recognize the image. The simulation results show that the proposed denoising and sharpening algorithms can process images well and improve the quality of images. The support vector machine is used to classify the image features processed by sift algorithm and PCA algorithm, and the automatic recognition of power equipment is realized. And the method of power identification based on image processing proposed in this paper has good recognition accuracy.

关键词： Power equipment Image processing sift algorithm PCA algorithm Support vector machine

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A probabilistic classifier for olfactory receptor pseudogenes

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BMC BIOINFORMATICS 2006年第1期7卷 393-393页

作者： Menashe, Idan Aloni, Ronny Lancet, Doron Weizmann Inst Sci Dept Mol Genet IL-76100 Rehovot Israel Weizmann Inst Sci Crown Human Genome Ctr IL-76100 Rehovot Israel

Background: Olfactory receptors (ORs), the largest mammalian gene superfamily (900-1400 genes), has > 50% pseudogenes in humans. While most of these inactive genes are identified via coding frame (nonsense) disruptions, seemingly intact genes may also be inactive due to other deleterious (missense) mutations. An ultimate assessment of the actual size of the functional human OR repertoire thus requires an accurate distinction between genes and pseudogenes. Results: To characterize inactive ORs with intact open reading frame, we have developed a probabilistic Classifier for Olfactory Receptor Pseudogenes (CORP). This algorithm is based on deviations from a functionally crucial consensus, constituting sixty highly conserved positions identified by a comparison of two evolutionarily-constrained OR repertoires ( mouse and dog) with a small pseudogene fraction. We used a logistic regression analysis to assign appropriate coefficients to the conserved position and thus achieving maximal separation between active and inactive ORs. Consequently, the algorithms identified only 5% of the mouse functional ORs as pseudogenes, setting an upper limit of 0.05 to the false positive detection. Finally we used this algorithm to classify the 384 purportedly intact human OR genes. Of these, 135 were predicted as likely encoding non-functional proteins, and 38 were segregating between active and inactive forms due to missense polymorphisms. Conclusion: We demonstrated that the CORP algorithm is capable to distinguish between functional and non-functional OR genes with high precision even when the encoded protein would differ by a single amino acid. Using the CORP algorithm, we predict that similar to 70% of human OR genes are likely non-functional pseudogenes, a much higher number than hitherto suspected. The method we present may be employed for better annotation of inactive members in other gene families as well.

关键词： Intact Gene sift algorithm Missense SNPs Intact Open Reading Frame Conservation Core

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Obstacle avoidance for small UAVs using monocular vision

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AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY 2011年第6期83卷 397-406页

作者： Lee, Jeong-Oog Lee, Keun-Hwan Park, Sang-Heon Im, Sung-Gyu Park, Jungkeun Konkuk Univ Seoul South Korea Pohang Inst Intelligent Robot Gyeongbuk South Korea

Purpose - The purpose of this paper is to propose that the three-dimensional information of obstacles should be identified to allow unmanned aerial vehicles (UAVs) to detect and avoid obstacles existing in their flight path. Design/methodology/approach - First, the approximate outline of obstacles was detected using multi-scale-oriented patches (MOPS). At the same time, the spatial coordinates of feature points that exist in the internal outline of the obstacles were calculated through the scale-invariant feature transform (sift) algorithm. Finally, the results from MOPS and the results from the sift algorithm were merged to show the three-dimensional information of the obstacles. Findings - As the method proposed in this paper reconstructs only the approximate outline of obstacles, a quick calculation can be done. Moreover, as the outline information is combined through sift feature points, detailed three-dimensional information pertaining to the obstacles can be obtained. Practical implications - The proposed approach can be used efficiently in GPS-denied environments such as certain indoor environments. Originality/value - For the autonomous flight of small UAVs having a payload limit, this paper suggests a means of forming three-dimensional information about obstacles with images obtained from a monocular camera.

关键词： Small UAVs sift algorithm MOPS Monocular vision Obstacle avoidance Image processing Collisions

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