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检索条件"任意字段=2nd International Conference on Computer Vision and Image Processing, CVIP 2017"

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Brain visual state classification of fMRI data using fuzzy support vector machine 2nd

Brain visual state classification of fMRI data using fuzzy s...

引用

2nd international conference on Advanced Computing and Intelligent Engineering, ICACIE 2017

作者： Kavitha, S. Bharathi, B. Pravish, S. Purushothaman, S.S. Department of Computer Science & Engineering SSN College of Engineering KalavakkamTamil Nadu India

ISBN: (纸本)9789811302237

The fMRI (Functional Magnetic Resonance Imaging) technology is a revolutionary tool that has lit up the studies of human cognitive processing with the help of efficient methods of image and data analysis. Machine learning classifiers are widely employed to extract all sorts of information from neuroimaging data. This study aims to identify tangible patterns in the fMRI data for visual activity and perform multivariate pattern analysis. It is done by selecting relevant features to indicate the response to visual stimulus of a set of objects belonging to eight different categories. The task intends to identify the nature of the response to the stimuli and classify them according to the brain’s neural activation to the visual stimuli. An SVM (Support Vector Machine) classifier and an FSVM (Fuzzy Support Vector Machine) classifier are implemented to perform the classification based on the features. The training of the classifiers involved 72 test samples per category. The 24 test samples of each category were tested with each of the classifiers. Conclusively, for this dataset, the FSVM classifier performs better than SVM classifier with an increased accuracy of 4% and classifying certain categories with improvement. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Colorblind image Correction Based on Segmentation and Similarity Judgement 2

Colorblind Image Correction Based on Segmentation and Simila...

引用

2018 2nd international conference on computer Graphics and Digital image processing, CGDIP 2018

作者： Ye, Rong Li, Ce No.187 Hubinbei Road Xiamen China Xueyuan Road Haidian District Beijing China

Color blindness is the common disease of color vision deficiency (CVD), mainly caused by the heredity. Suffering from color blindness, a significant percentage of population faces the difficulty of recognizing color-based information. In this paper, we propose a colorblind image correction algorithm to accommodate digital images for color vision deficiency users. The algorithm has two parts: 1) image segmentation by K-means and system-clustering algorithms;and 2) image correction based on similarity judgement and multi-factor selection of color replacement. We then test the efficacy of our algorithm through simulations. © Published under licence by IOP Publishing Ltd.

关键词： Color vision

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Integrated feature exploration for handwritten devanagari numeral recognition 1

引用

2nd international conference on computer vision and image processing, cvip 2017

作者： Arya, Shraddha Chhabra, Indu Lehal, G.S. Department of Computer Science Sri Guru Gobind Singh College Chandigarh India Department of Computer Science and Applications Panjab University Chandigarh India Computer Science Department Punjabi University PatialaPunjab India

ISBN: (数字)9789811078958

ISBN: (纸本)9789811078941

In this paper, the statistical feature extraction techniques are explored, incrementally combined using different methods and analyzed for the recognition of isolated offline handwritten Devanagari numerals. The techniques selected are zoning, directional distance distribution, Zernike moments, discrete cosine transform, and Gabor filter that encapsulate the mutually exclusive statistical features like average pixel densities, directional distribution, orthogonal invariant moments, elementary frequency components, and space frequency component, respectively. The standard benchmark handwritten Devanagari numeral database provided by ISI, Kolkata, is used for the experimentation and 1-nearest neighbor and support vector machine for classification. The accuracy achieved with individual feature extraction techniques ranges from 86.87% to 98.96%. Further, features are integrated with methods like feature concatenation, majority voting, and a new proposed methodology by us named winners pooling. The maximum recognition obtained through feature integration is 99.14%. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Gabor filters

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Obtaining Ellipse Common Tangent Line Equations by the Rolling Tangent Line Method 2nd

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2nd international conference on Machine Learning and Intelligent Communications, MLICOM 2017

作者： Feng, Naizhang Jiang, Teng Duan, Shiqi Sun, Mingjian School of Information and Electrical Engineering Harbin Institute of Technology West Wenhua Road 2 High-tech District WeihaiShandong264209 China

ISBN: (纸本)9783319734460

In the field of image processing and machine vision, it is sometimes necessary to obtain common tangent line equations and tangent point coordinates from ellipses. A rolling tangent line method was proposed to obtain the 4 common tangent line equations and 8 tangent point coordinates from two ellipses in this paper. The principle of this method is simple and it is easy to program on a computer. Use this method to process two ellipse targets in an image and the experiment results show that the 4 common tangent equations and 8 tangent point coordinates can be obtained in high precision and the maximum execution time is less than 0.1 s. © 2018, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： computer vision

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Detecting Both Machine and Human Created Fake Face images In the Wild 2

Detecting Both Machine and Human Created Fake Face Images In...

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2nd international Workshop on Multimedia Privacy and Security (MPS)

作者： Tariq, Shahroz Lee, Sangyup Kim, Hoyoung Shin, Youjin Woo, Simon S. SUNY Korea Incheon South Korea

ISBN: (纸本)9781450359887

Due to the significant advancements in image processing and machine learning algorithms, it is much easier to create, edit, and produce high quality images. However, attackers can maliciously use these tools to create legitimate looking but fake images to harm others, bypass image detection algorithms, or fool image recognition classifiers. In this work, we propose neural network based classifiers to detect fake human faces created by both 1) machines and 2) humans. We use ensemble methods to detect GANs-created fake images and employ pre-processing techniques to improve fake face image detection created by humans. Our approaches focus on image contents for classification and do not use meta-data of images. Our preliminary results show that we can effectively detect both GANs-created images, and human-created fake images with 94% and 74.9% AUROC score.

关键词： Generative Adversarial Network Fake image Detection image Forensics

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D-PNR: Deep license plate number recognition 1

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2nd international conference on computer vision and image processing, cvip 2017

作者： Kumar, Krishan Sinha, Shambhavi Manupriya, Piyushi Department of Computer Science and Engineering NIT Uttarakhand India

ISBN: (数字)9789811078989

ISBN: (纸本)9789811078972

Deep learning empowered the license plate recognition (LPR) system which can efficiently extract the information from a vehicle’s license plate. LPR has various applications in this digital world. Due to technology growing at a rocketing pace, there is a rapid growth in the number of vehicles on road. Even self-driving cars are soon to be a common sight. This is causing a fast and frequent growth in the accidents occurrence and other mishaps. Thus, there is a need for monitoring traffic and security surveillance. LPR technique is not new. However, traditionally the extracting features from an image/license plate were done hand-tunned which make the recognition process time-consuming and error-prone. In this paper, we proposed a novel machine learning approach to recognizing the license plate number. We used one of the most successful deep learning method, convolutional neural network (CNN) for extracting the visual features automatically. Suitable localization and segmentation techniques are employed before CNN model to enhance the accuracy of the proposed model. In addition to this, the D-PNR model also takes care of proper identification from images those are hazy and is not suitable-inclined or noisy images. Qualitative and quantitative evaluation is done in order to compare the performances of the proposed D-PNR model and state-of-the-art models. A computing analysis of our approach also shows that it meets the requirement of the real-time applications, i.e., monitoring traffic and security surveillance. © Springer Nature Singapore Pte Ltd. 2018.

关键词： License plates (automobile)

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Realization of Traffic Video Surveillance on DM3730 Chip 2nd

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2nd international conference on Machine Learning and Intelligent Communications, MLICOM 2017

作者： Zhang, Xin Dong, Hang College of Electronics and Information Engineering Tongji University Dianxin Building Jiading District Shanghai China

ISBN: (纸本)9783319734460

A general method for traffic video surveillance task involves foreground detecting and moving objects’ tracking. The Gaussian mixture model is generally used in detecting foreground and the Kalman filter is used in multi-objects tracking. This paper has implemented a multi-objects tracking system using DM3730 development board as the hardware platform, which is powerful at image processing and analysis. This paper will adopt an Open computer vision library (OpenCV) to efficiently implement the overall system. The OpenCV library with a large amount of optimized algorithms in computer vision and machine learning will facilitate the realization of the system. The testing results demonstrate the effectiveness of the system through tracking of vehicles. © 2018, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： computer vision

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Paper piano-Shadow analysis based touch interaction 2

Paper piano-Shadow analysis based touch interaction

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2nd international conference on Man and Machine Interfacing, MAMI 2017

作者： Vishal, Boga Lawrence, K Deepak Department of Electronics and Communication Manipal Institute of Technology Manipal India Department of Aeronautical and Automobile Engineering Manipal Institute of Technology Manipal India

ISBN: (纸本)9781538629895

Recent years have marked a sharp increase in the number of ways in which people interact with electronic devices. Keyboards and computer mouse devices are not the only way users interact with their computers. This paper aims to investigate and demonstrate a human-computer interaction application in which a user can interact with the layout of a piano on a sheet of paper using computer vision. The image is acquired using a general-purpose camera from a single direction. The work presents details about methods of piano key detection and labelling, hand movement detection, fingertip detection and tracking, and touch interaction based on the shadow of the finger. K-means clustering is used to segment the hand and its shadow. Contour analysis is used in determining the shape and position of the keys. Shadow analysis aids in determining if the finger is touching the paper, even without any depth data from the camera. The detected key press then triggers a sound. The paper covers the details of the development of the virtual piano from concept to realization. © 2017 IEEE.

关键词： image segmentation

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Cost Effective Real Time vision Interface for Off Line Simulation of Fanuc Robots

Cost Effective Real Time Vision Interface for Off Line Simul...

引用

international conference on Signal processing and Information Security (ICSPIS)

作者： Bittu Scaria Nazarudeen A. Aziz Alavikunhu Panthakkan College of Engineering Khalifa University Abu Dhabi UAE College of Engineering & IT University of Dubai Dubai UAE

ISBN: (数字)9781728138732

ISBN: (纸本)9781728138749

The proliferation of automation has created an increasing demand for robots in every area of the manufacturing industry. FANUC robots are very widely used in automated production lines because of its intelligent functions with flexible open architecture. It allows the users to plugin online additional components such as vision and sensor systems to support the development of robotic systems. FANUC also has an offline simulation tool called Roboguide, which allows the users to simulate a virtual robotic cell in 3D, eliminating the need for expensive physical prototype setup. This tool supports the virtual integration of an integral Robot vision (iRvision) capabilities. However, this feature is limited to virtual vision or using very expensive FANUC compatible cameras that allow the users to take a real mode image and simulate it in the virtual world. In this paper, we propose an offline plugin for interfacing normal cameras of any type including webcams to the FANUC iRvision system for the virtual simulation of real mode images. It was developed using an Open computer vision (OCV) plugin and tested it by physically capturing the real image of the object using a webcam interfaced with the iRvision system and processed it on the virtual robot controller. The test results show that this cost-effective plugin can be used as an OCV in industrial automation and robotic building system without any compromise in terms of performance and quality.

关键词： Tools Cameras Robot vision systems Service robots Calibration

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The Light Plane Calibration Method of the Laser Welding vision Monitoring System 2

The Light Plane Calibration Method of the Laser Welding Visi...

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2nd international conference on Mechatronics and Electrical Systems (ICMES)

作者： Wang, B. G. Wu, M. H. Jia, W. P. Dalian Univ Coll Mech Engn Lab Nontradit Machining & Funct Mat Preparing Dalian 116622 Peoples R China

According to the aerospace and automobile industry, the sheet steels are the very important parts. In the recent years, laser welding technique had been used to weld the sheet steel part. The seam width between the two parts is usually less than 0.1mm. Because the error of the fixture fixed can't be eliminated, the welding parts quality can be greatly affected. In order to improve the welding quality, the line structured light is employed in the vision monitoring system to plan the welding path before welding. In order to improve the weld precision, the vision system is located on Z axis of the computer numerical control (CNC) tool. The planar pattern is placed on the X-Y plane of the CNC tool, and the structured light is projected on the planar pattern. The vision system stay at three different positions along the Z axis of the CNC tool, and the camera shoot the image of the planar pattern at every position. Using the calculated the sub-pixel center line of the structure light, the world coordinate of the center light line can be calculated. Thus, the structured light plane can be calculated by fitting the structured light line. Experiment result shows the effective of the proposed method.

关键词： Laser beam welding

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