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检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

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Real Time Hand Gesture Recognition for Human computer Interaction

Real Time Hand Gesture Recognition for Human Computer Intera...

引用

IEEE international Advance Computing conference, IACC

作者： Rishabh Agrawal Nikita Gupta Department of Computer Engineering Savitribai Phule Pune University Maharashtra India

ISBN: (纸本)9781467382878

Most of the human computer interaction interfaces that are designed today require explicit instructions from the user in the form of keyboard taps or mouse clicks. As the complexity of these devices increase, the sheer amount of such instructions can easily disrupt, distract and overwhelm users. A novel method to recognize hand gestures for human computer interaction, using computer vision and image processing techniques, is proposed in this paper. The proposed method can successfully replace such devices (e.g. keyboard or mouse) needed for interacting with a personal computer. The method uses a commercial depth + rgb camera called Senz3D, which is cheap and easy to buy as compared to other depth cameras. The proposed method works by analyzing 3D data in real time and uses a set of classification rules to classify the number of convexity defects into gesture classes. This results in real time performance and negates the requirement of any training data. The proposed method achieves commendable performance with very low processor utilization.

关键词： Gesture recognition Cameras Human computer interaction Real-time systems Mice Thumb

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An Aerocraft Photogrammetry Position Sensing System

An Aerocraft Photogrammetry Position Sensing System

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2016 IEEE international conference on Signal and image processing

作者： Tao Xu Chao Yang Bin Cai Yongli Zhu Aviation System Research Dept.System Engineering Research Institute

Landing aerial crafts, such as helicopters, on the board of naval vessels of small or medium size is a difficult and risky task for pilots since the tonnages are not large enough which makes the ships always swinging along with ocean *** the landing areas are moving all the way with six degrees of freedom ***, this mission will become dangerous and deadly when the weather is ***, we design a real-time and automatic position sensing system to track, locate and help a helicopter to land on deck safely under all weather *** the sake of practical application, we have not only adopted some ready and mature computational technologies from image processing, photogrammetry and computer vision, but also chosen some simple but effective optical elements to reduce the computational *** system is composed of camera units, image-processing unit, controlling system and fiber optical communication *** results show our system is capable of all-weather, real-time, robust and automatic landing mission.

关键词： Photogrammetry position sensing camera calibration image processing

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Particle swarm optimization enabled filtering for fabric images in automated fabric inspection system

Particle swarm optimization enabled filtering for fabric ima...

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international conference on Computing for Sustainable Global Development (INDIACom)

作者： S. Sahaya Tamil Selvi Dept. of Computer Science St. Joseph's College for Women Tirupur India

ISBN: (纸本)9781467394178

Random variations in intensity, poor contrast, variations in illumination are the common reasons for the images to be usually corrupted. These corruptions must be handled by the early stages of vision processing. Even though there are wide varieties of filtering techniques available for the purpose of removing noise in digital images, the problem still remains challenging in research. This paper shows how, Particle Swarm Optimization (PSO) enabled filtering method has been implemented and its performance is compared with the other filtering techniques such as Median, Gaussian filtering methods. The performances of these filtering methods on digital fabric images are assessed based on the metrics Mean squared error (MSE) and Peak signal to noise ratio (PSNR). The implementation results are then compared and evaluated.

关键词： Filtering Fabrics Digital images Inspection conferences Measurement image processing

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Using the 5th dimensions of human visual perception to inspire automated edge and texture segmentation: A fuzzy spatial-taxon approach

Using the 5th dimensions of human visual perception to inspi...

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IEEE international conference on Cognitive Informatics

作者： Lauren Barghout Visiting Scholar at Berkeley Initiative for Soft Computing Electrical Engineering and Computer Science University of California at Berkeley Berkeley CA USA

ISBN: (纸本)9781509038473

With the recent stunning success of machine learning, artificially intelligent machine vision research falls (roughly) into two camps: the big data camp and cognitive informatics camp. Big data uses statistical methods to discover latent structures that emerge from the co-occurrences of relevant features when sampling over enormous quantities of data. The cognitive informatics methods design computer vision systems to mimic human cognition. Though some visual latent features that emerge from deep learning networks, mimic mammalian visual detectors, as of yet the information processing mechanisms (analogous to human psychophysical mechanisms) remain hidden within the complexity of the deep nets. Furthermore, the sampling requirements of big data systems require limiting samples to pre-processed sets, such as SHIFT (shift invariant feature transform (Lowe 1999)). Techniques, such as the ones introduced in this paper, provide fast cognitively relevant methods for selecting samples and reducing the number of candidate features. The approach described in this paper live squarely in the camp of designing computer vision A.I. to mimics human cognitive processes. I introduce a novel definition of edges, based on human hierarchical scene perception. Hierarchical scene perception views vision within the 5 dimensions of horizontal & vertical position, depth, time and scene abstraction level (spatial-taxon). Fuzzy inference selects candidate edge elements using the Gestalt psychology principal of good curvilinear continuation, proximity and edges attachment. Spatial-taxon inference infers an edge outline for each level of abstraction within the scene architecture. The system was tested on 60 natural images and the results provide edges more aligned with human intuition of what edges should look like. ROC plots indicate solid performance, with the majority of human subjects rating the edge detection as high quality. The inferred edges are consistent with the finding of neurons r

关键词： image edge detection computer vision Laplace equations Big data image segmentation Cognitive informatics Visualization

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Dynamic hand gesture recognition using kinect sensor

Dynamic hand gesture recognition using kinect sensor

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international conference on Global Trends in Signal processing, Information Computing and Communication (ICGTSPICC)

作者： Devendrakumar H. Pal S. M. Kakade Electrical Engineering Department College of Engineering Pune Pune India

ISBN: (纸本)9781509004683

Continuous trajectory path made by hand over a period of time is considered for gesture recognition purpose. Dynamic gesture recognition has always been critical, since conventional method utilize separation of hand from surrounding environment and then finding of palm points make it hard. In this paper real time dynamic hand gesture recognition system using kinect sensor has been proposed. In this the movement of human hand will be captured by kinect sensor and it will be processed in OpenCV. Signal generated by OpenCV are given to Arduino and it will be utilized for controlling DC servo motor action. The computer will generate appropriate signals for controlling the action of robotic arm. The movements of robotic arm links are controlled by DC servo motors. Real-time hand tracking technique is used for object detection in the range of vision.

关键词： Hidden Markov models Robot sensing systems Manipulators Gesture recognition Feature extraction image color analysis

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A visual object tracking algorithm based on the game of features

A visual object tracking algorithm based on the game of feat...

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international conference on Wireless Communications and Signal processing (WCSP)

作者： Zefenfen Jin Zhiqiang Hou Xianglin Wang Wangsheng Yu Xin Wang Air Force Engineering University Information and Navigation Institute Xi'an China

ISBN: (纸本)9781509028610

Aim at improving the robustness by employing single feature tracking algorithm in visual object tracking realm, we put forward an object tracking algorithm based on the thought of game theory via multi-feature fusion. Under the framework of Mean Shift visual tracking, treating the color features and motion features expressed by optical flow as two gamers, by searching the Nash Equilibrium of their game, makes various feature's contribution reach the optimum balance, then the advantages of feature fusion are reflected better. According to experimental results, this algorithm is robust to the drastic motion of object, obstacle occlusion and background interference. This study proposes a new algorithm, which base on traditional Mean Shift algorithm and use multi-feature fusion with game theory. The algorithm shows a good tracking performance.

关键词： Histograms Tracking computer vision image motion analysis Optical reflection Color Optical imaging

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Automated enhancement and detection of stripe defects in large circular weft knitted fabrics

Automated enhancement and detection of stripe defects in lar...

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international conference on Emerging Technologies and Factory Automation (ETFA)

作者： Marcin Kopaczka Hanry Ham Kristina Simonis Raphael Kolk Dorit Merhof Institute for Imaging and Computer Vision RWTH Aachen University Aachen Germany King Mongkut's University of Technology North Bangkok Sirindhorn International Thai-German Graduate School of Engineering Bangkok Thailand Institut für Textiltechnik RWTH Aachen University Aachen Germany

ISBN: (纸本)9781509013159

Stripes are periodic defects that are difficult to detect during production even by experienced human inspectors. Therefore, we introduce an image processing method for automatically detecting stripe defects in circularly knitted fabric. We show how a barely visible defect can be optically enhanced to improve manual assessment as well as how descriptor-based image processing and machine learning can be used to allow automated stripe detection. image enhancement is performed by applying gabor and matched filters to histogram-equalized fabric images. Subsequently, we extract image information with different descriptors (LBP, GLCM, HOG) and feed these into random forest and SVM classifiers. The full pipeline is validated by training and testing it on three sets of fabric produced with different knitting machines and parameter settings. Results show that the proposed enhancement combined with a statistics-based descriptor such as GLCM or HOG allows to train both tested classifiers with good classification rates of up to 98.9%.

关键词： Fabrics Support vector machines Yarn Radio frequency Production Pipelines Feature extraction

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A Faber Schauder dominant blocks based fragile watermarking scheme for image tamper detection 2nd

A Faber Schauder dominant blocks based fragile watermarking ...

引用

international conference on Electrical and Information Technologies (ICEIT)

作者： Assma Azeroual Karim Afdel Faculty of science Agadir Computer Systems and Vision Laboratory Morocco

ISBN: (纸本)9781467384704

The need of digital content authentication is increasing, due to the easier the digital content modification becomes, that is owing to the technology development. Several fragile watermarking based methods have been proposed to authenticate image. In such methods, a mark is embedded into the digital image to authenticate it. There is a few methods that deal with algorithm complexity, hence it can not be used for the applications that require low complexity such as real-time applications and video processing applications. We propose in this paper, a Faber Schauder dominant blocks based fragile watermarking scheme for image tamper detection. The Watermark was generated by applying Xor operation between a logo's bits and the bits of dominant blocks singular values of the image to authenticate. These dominant blocks are obtained by applying Faber Schauder Discrete Wavelet Transform (FSDWT) to that image. Since the image is characterized by its contours and its around textures which contain an important concentration of dominant coefficients -that form dominant blocks-, any image modification will result in a significant change of the dominant blocks singular values, which lead to detect the authenticity of the image. Furthermore, FSDWT is composed of simple operations, thus the algorithm have a low complexity. Experimental results and analysis demonstrate the effectiveness of the proposed method.

关键词： Watermarking Authentication Complexity theory Transforms Information technology Algorithm design and analysis Matrix decomposition

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A semi automatic geometric active contour model using Distance Regularized term for segmentation of abdominal organs on CT images

A semi automatic geometric active contour model using Distan...

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IEEE international conference on Engineering and Technology (ICETECH)

作者： S. M. AnchaloBensiger S.N Kumar A. Lenin Fred S. Lalitha Kumari Mar Ephraem College of Engineering and Technology Marthandam Tamil Nadu India Sathyabama University Chennai Tamil Nadu India Mar Ephraem College of Engineering and Technology Tamil Nadu India Sathyabama University Chennai Tamil Nadu IN

Level set models are widely used in image processing and computer vision for segmentation. In this paper, an improved geometric active contour model is used for the segmentation of abdominal organs in abdomen CT images. The pre-processing of input images was done by anisotropic diffusion filter that effectively preserve the edges. The proposed Distance Regularized Level set Evolution (DRLSE) doesn't requires initialization procedure unlike the conventional level set methods. The distance regularized term is defined using double well potential function such that the level set evolution has unique forward and backward diffusion (FAB) diffusion effect, which is able to maintain a desired shape of the level set function. The algorithms were developed in Matlab 2010 and tested on real time CT data sets.

关键词： Level set image segmentation Computed tomography Active contours Anisotropic magnetoresistance Mathematical model Biomedical imaging

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Open CV pattern based smart bank security system with theft & identification using Android

Open CV pattern based smart bank security system with theft ...

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international conference on Applied and Theoretical Computing and Communication Technology (iCATccT)

作者： Blessed Joshua A. Jenita Grace J. Allan Mary George Department of Biomedical Engineering Alpha College of Engineering Chennai

ISBN: (纸本)9781509024001

Authentication is a major problem experienced by an individual in their daily activities especially in banking system. The security provided by bank systems has some backdoors, which are improved by using other techniques like the pattern recognition comparing these existing traits, there is still need for considerable computer vision. Pattern recognition is a particular type of biometric system that can be used to analyze the obtained information and identify the user uniquely by the stored pattern produced in the OPEN CV image processing used in the security systems. In this proposed system the pattern is collected in the form of dataset, stored and is maintained in the bank's server. A camera is in build in the machine which captures the data and relay the data for processing features of the logic was compared and user where recognized. In addition to the authentication of user there is another system to identify the user before that RFID tag checking is Password entry through mobile phone is needed for another level of security. This can be done by using Bluetooth and also authentication is checked by verification through UIN number.

关键词： GSM Bluetooth DC motors image recognition Robustness Microcontrollers Radio frequency

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