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International Conference on Robotics and Intelligent System (ICRIS)

作者： Zhang, Yi Zhang, Han Xu, Xiaodong Dai, Jianchu Chongqing Univ Post & Telecommun Chongqing Peoples R China

ISBN: (纸本)9781538665800

In order to solve the problem of low efficiency in the process of locating objects when the industrial robot performs a crawling operation, a hierarchical object localization strategy combining MeanShift algorithm and surf algorithm is proposed to locate the objects quickly and accurately. Firstly, the MeanShift algorithm is used for cutting out the target image information for initial processing, according to the target object image information collected by the binocular vision system. Then, the feature points are matched by the surf algorithm with good computational superiority and repeatability, uniqueness and robustness. Finally, the matching feature points are combined with the triangular measurement principle to accurately locate the threedimensional coordinates of the object. The experiment proves that the method of this paper has improved the speed and precision of the recognition of the robot crawling.

关键词： MeanShift algorithm surf algorithm Feature matching Trianglemeasurement principle Binocular vision.

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Research on Feature Matching algorithm Based on Three-dimensional Information Acquisition

Research on Feature Matching Algorithm Based on Three-dimens...

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International Conference on Computer Science and Network Technology (ICCSNT)

作者： Zong, Xiaoning Li, Xinzhi Tianjin Univ Technol Tianj Key Lab Control Theory & Applicat Complicat Tianjin Peoples R China Tianjin Design & Res Inst Elect Dr Tianjin Peoples R China

ISBN: (纸本)9781457715846

Image feature matching in three-dimensional information acquisition technology is an important aspect of machine vision, in order to achieve the real-time and matching robustness requirement, an image registration method based on surf algorithm is proposed. First construct Hessian matrix based on box-type filter, use surf algorithm to calculate the information of feature points, then decompose characteristics of feature points and match feature points. Experimental results show that the matching speed of surf algorithm is 4 times as fast as the SIFT algorithm, greatly improves the real-time and robustness.

关键词： three-dimensional information acquisition surf algorithm image registration

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Tracking Landmarks for Control of an Electric Wheelchair Using a Stereoscopic Camera System

Tracking Landmarks for Control of an Electric Wheelchair Usi...

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International Conference on Advanced Technologies for Communications (ATC)

作者： Ngo Ba Viet Nguyen Thanh Hai Nguyen Viet Hung UTE HCMC Fac Elect Elect Engn Ho Chi Minh City Vietnam Int Univ VNU HCMC Biomed Engn Dept Ho Chi Minh City Vietnam

ISBN: (纸本)9781479910861;9781479910885

An electrical wheelchair developed to operate in the indoor environments automatically avoids obstacles to move to the desired target for severely disabled people using a stereoscopic camera system. This paper presents a self-propelled control algorithm based on landmarks numbered in order. A surf algorithm was applied to identify the landmark position, at the same time the "Bumblebee" camera was used to determine the depth parameter of the environmental images for control calculation. Based on this information, the wheelchair can locate where it is by using geometric projection algorithm. The results showed that the wheelchair automatically detected the landmarks to reach the desired target. This means that the proposed method is reliable and effective.

关键词： Electrical wheelchair stereoscopic camera system surf algorithm obstacle avoidance

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A Deterministic Compressive Sensing Approach for Compressed Domain Image Analysis

A Deterministic Compressive Sensing Approach for Compressed ...

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IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Mitra, Dipayan Rajan, Sreeraman Balaji, Bhashyam Carleton Univ Dept Syst & Comp Engn Ottawa ON Canada Def R&D Canada 3701 Carling Ave Ottawa ON Canada

ISBN: (纸本)9781538675687

Compressive sensing (CS) is a signal processing technique for acquiring sparse signals at sampling rates much lower than the Nyquist rate. Traditionally to avoid generation of large sensing matrices for 2D signals or images, individual rows or columns of the images are compressed in the sensing phase. This increases the number of matrix multiplication operations and results in a compressed image with a different aspect ratio than the original uncompressed image. To overcome these issues, in this paper, we investigate a 2D deterministic sensing technique that maintains both the aspect ratio and the morphology of the image. We use a linear filtering-based measurement matrix. Through this paper, we demonstrate that deterministic CS will preserve the features and there by enable analysis of the images such as detection and identification of objects in the compressed domain without the need to perform a computationally expensive reconstruction. In order to demonstrate this, images obtained by infra-red electro-optic camera on an airborne platform (low resolution), LandSat (medium resolution) and multispectral images (high resolutions) are chosen. Features of chosen objects from an uncompressed image are compared with those corresponding objects in the compressed image using template matching to demonstrate that such image analysis can be done in the compressed domain. Frobenius norm-based structural similarity analysis for the images at different levels of compression is presented to demonstrate the similarity in structure. Robustness of the deterministic CS technique is shown by performing template matching based image analysis on noisy compressed images.

关键词： Compressive Sensing 2D Signal Processing Image Processing Feature Extraction Frobenius Norm surf algorithm

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Image Mosaic Based on surf and Results Optimization

Image Mosaic Based on SURF and Results Optimization

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2013年中国智能自动化学术会议

作者： Tie Jiang Guibin Zhu Chongqing Key Laboratory of Emergency Communication 13 teamChongqing Communication Institute

In order to improve the insufficiency of surf algorithm,we present an auto-adjusted algorithm of image size based on *** detect the zoom relationship and translation co-efficiency between the images and modulate the unregistrated image's scale to the same level as the original *** obtain the Region of Interest(ROI) according to the translation parameter and then pretreat the *** propose an image matching method based on the saliency *** calculate the saliency map in the Region of Interest and mark the interest points in the area by using surf *** the part of image fusion,the method of gradated in-and-out which we commonly use is improved to eliminate *** the image exposure differences,we propose two methods to adjust the exposure of spliced *** is based on mean value and the other is based on mean-variance *** the experiment,the validity of the proposed methods is demonstrated and the quality of the mosaic image is better.

关键词： Image mosaic Saliency map surf algorithm Mean value Mean-variance specification

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Video shot boundary detection method using histogram differences and local image descriptor 2

Video shot boundary detection method using histogram differe...

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2014 Second World Conference on Complex Systems (WCCS)

作者： Bendraou, Youssef Essannouni, Fedwa Aboutajdine, Driss Salam, Ahmed Univ Mohamed V Agdal Rabat GSCM LRIT Lab Associate Unit CNRST URAC 29 Fac Sci BP 1014 Rabat Morocco Univ Lille North France ULCO LMPA F-62228 Calais France

ISBN: (纸本)9781479946471

Video shot boundary detection is a fundamental component in automatic video indexing, archiving and editing. Different techniques have been developed in the past with reliable performances in the video processing, especially for the key frame extraction and video summarization. In this paper, we propose a new method for video cut detection in two steps. First, we calculate the histogram differences between each two consecutive frames. Afterwards, we define a thresholding selection that give a set of images candidates for which we adapt the surf algorithm to eliminate false detections. Experimental results are presented to illustrate the good performance of the proposed method with a pourcentage of 100% for the recall criterion.

关键词： Video shot boundary detection Histogram differences surf algorithm

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Medical image registration based on Clifford algebra and three-dimensional surf

Medical image registration based on Clifford algebra and thr...

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第32届中国过程控制会议(CPCC2021)

作者： Cheng Tianyu Gu Juping Hua Liang Zhou Bojun Zhao Fengshen Zhao Jiahao School of Automation Nanjing University of Science and Technology School of Electrical Engineering Nantong University

Multimodal medical image registration can provide doctors with more abundant focus information of patients,but there is a contradiction between registration accuracy and efficiency in clinical *** this paper,a 3 D surf framework based on Hessian four-dimensional scale space is built,a feature descriptor based on geometric algebraic relative angle invariants is designed,which is more suitable for 3 D images,and a fast spatial optimization(GA-FSO) algorithm based on this descriptor is *** method achieves high precision registration and compensates the lack of immediacy in clinical ***,the registration experiment is carried out based on the brain multimodal images provided by RIRE open database,and the mean error is less than 3 mm,which verifies the effectiveness of this registration scheme and satisfies demand of clinical online *** the contrastive experiments for registration are carried out with clinical case data to verify the clinical practicability of the registration *** study provides theoretical basis and technical support for the clinical application of three-dimensional multimodal medical image registration.

关键词： medical image registration geometric algebra surf algorithm feature descriptor fast space optimization

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Real-time Reconstruction of Unstructured Scenes Based on Binocular Vision Depth

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JOURNAL OF INTERNET TECHNOLOGY 2019年第5期20卷 1611-1623页

作者： Xie, Yinggang Xing, Jingyu Liu, Guangjun Lan, Jiangyu Dong, Yaoyao Beijing Informat Sci & Technol Univ Sch Informat & Commun Engn Beijing Peoples R China Ryerson Univ Dept Aerosp Engn Toronto ON Canada

Binocular vision is a method that simulates the principle of human vision and uses a computer to passively perceive distance. By obtaining the depth of field information of the object, the actual distance between the object and the camera can be calculated. Based on the improved surf (Speeded-Up Robust Features) algorithm, this paper implements image feature extraction from different perspectives. The image fusion based on improved Sobel algorithm is used to achieve image fusion and image feature point matching. The triangulation principle is used to calculate the offset between pixels to obtain the three-dimensional information of the object, reconstruct the three-dimensional coordinates, analyze the actual depth, establish the bad point culling rule based on the numerical relationship of the image sequence, and finally use the visual depth information to construct the unstructured 3D (3 dimensions) real-time scene. The experimental results show that for the target in the actual unstructured scene, the average error of 0.1m to 3m is 2.99%;the average error of 3m to 10m is 5.81%, and the system achieves higher measurement accuracy and better 3D reconstruction effect.

关键词： Binocular vision Three-dimensional reconstruction Visual depth surf algorithm

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A New Visual Inertial Simultaneous Localization and Mapping (SLAM) algorithm Based on Point and Line Features

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DRONES 2022年第1期6卷

作者： Zhang, Tong Liu, Chunjiang Li, Jiaqi Pang, Minghui Wang, Mingang Northwestern Polytech Univ Unmanned Syst Res Inst Xian 710072 Peoples R China Syst Engn Inst Sichuan Aerosp Chengdu 610100 Peoples R China Northwestern Polytech Univ Sch Astronaut Xian 710072 Peoples R China

In view of traditional point-line feature visual inertial simultaneous localization and mapping (SLAM) system, which has weak performance in accuracy so that it cannot be processed in real time under the condition of weak indoor texture and light and shade change, this paper proposes an inertial SLAM method based on point-line vision for indoor weak texture and illumination. Firstly, based on Bilateral Filtering, we apply the Speeded Up Robust Features (surf) point feature extraction and Fast Nearest neighbor (FLANN) algorithms to improve the robustness of point feature extraction result. Secondly, we establish a minimum density threshold and length suppression parameter selection strategy of line feature, and take the geometric constraint line feature matching into consideration to improve the efficiency of processing line feature. And the parameters and biases of visual inertia are initialized based on maximum posterior estimation method. Finally, the simulation experiments are compared with the traditional tightly-coupled monocular visual-inertial odometry using point and line features (PL-VIO) algorithm. The simulation results demonstrate that the proposed an inertial SLAM method based on point-line vision for indoor weak texture and illumination can be effectively operated in real time, and its positioning accuracy is 22% higher on average and 40% higher in the scenario that illumination changes and blurred image.

关键词： simultaneous localization and mapping (SLAM) fast bilateral filtering surf algorithm nearest-neighbor algorithm geometric constraints feature extraction

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Offline Signature Recognition and Forgery Detection using Deep Learning

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Procedia Computer Science 2020年 170卷 610-617页

作者： Jivesh Poddar Vinanti Parikh Santosh Kumar Bharti Pandit Deendayal Petroleum University Gandhinagar Gujarat India

Authentication plays a very important role to manage security. In the modern era, it is one, in all the priorities. With the appearance of technology, the interaction with machines is turning automatic. Therefore, the need of authentication increases rapidly for various security purposes. Because of this, the biometric-based authentication has gained a drastic momentum. It is a kind of boon over other techniques. However, this event is not a replacement of drawback but varied ways are adopted to verify folks. Signature is one of the first broadly practiced biometric features for the verification of an individual. This paper proposes a method for the pre-processing of signatures to make verification simple. It also proposed a novel method for signature recognition and signature forgery detection with verification using Convolution Neural Network (CNN), Crest-Trough method and surf algorithm & Harris corner detection algorithm. The proposed system attains an accuracy of 85-89% for forgery detection and 90-94% for signature recognition.

关键词： Signature Verification Forgery Detection CNN Signature Recognition surf algorithm Harris algorithm

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