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GUESS: Genetic uses in video encryption with secret sharing 1

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

作者： Sharma, Shikhar Kumar, Krishan Department of Computer Science & Engineering NIT SrinagarUttarakhand India

ISBN: (数字)9789811078958

ISBN: (纸本)9789811078941

Nowadays, video security systems are essential for supervision everywhere, for example video conference, WhatsApp, ATM, airport, railway station, and other crowded places. In multi-view video systems, various cameras are producing a huge amount of video content which makes it difficult for fast browsing and securing the information. Due to advancement in networking, digital cameras, and media, interactive sites, the importance of privacy and security is rapidly increasing. Hence, nowadays the security of digital videos become an emerging research area in the multimedia domain;especially when the communication happens over the Internet. Cryptography is an essential practice to protect the information in this digital world. Standard encryption techniques like AES/DES are not optimal and efficient in case of videos. Therefore, a technique is immediately required, which can provide the security to video content. In this paper, we address the video security-related issues and their solutions. An optimized version of the genetic algorithm is employed to solve the aforementioned issues through modeling the simplified version of genetic processes. It is used to generate a frame sequence such that the correlation between any two frames is minimized. The frame sequence determines the randomization in order of frames of a video. The proposed method is not only fast but also more accurate to enhance the efficiency of an encryption process. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Cryptography

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Comparative Analysis of Emotion Detection from Facial Expressions and Voice Using Local Binary Patterns and Markov Models 2018

Comparative Analysis of Emotion Detection from Facial Expres...

引用

2nd international conference on vision, image and Signal processing (ICVISP)

作者： Chengeta, Kennedy Univ KwaZulu Natal Sch Comp Sci & Math Westville Campus Durban South Africa

ISBN: (纸本)9781450365291

Emotion detection has been achieved widely in facial and voice recognition separately with considerable success. The 6 emotional categories coming out of the classification include anger, fear, disgust, happiness and surprise. These can be infered from one's facial expressions both in the form of micro and macro expressions. In facial expressions the emotions are derived by feature extracting the facial expressions in different facial poses and classifying the expression feature vectors derived. Similarly automatic classification of a person's speech's affective state has also been used in signal processing to give insights into the nature of emotions. Speech being a critical tool for communication has been used to derive the emotional state of a human being. Different approaches have been successfully used to derive emotional states either in the form of facial expression recognition or speech emotional recognition being used. Less work has looked at fusing the two approaches to see if this improves emotional recognition accuracy. The study analyses the strengths of both and also limitations of either. The study reveals that emotional derivation based on facial expression recognition and acoustic information complement each other and a fusion of the two leads to better performance and results compared to the audio or acoustic recognition alone.

关键词： Berlin Emotional Database Local Binary Patterns Facial Recognition

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Deep Learning Approach for image Classification 2

Deep Learning Approach for Image Classification

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2nd international conference on Data Science and Business Analytics (ICDSBA)

作者： Panigrahi, Santisudha Nanda, Anuja Swamkar, Tripti Siksha O Anusandhan Dept Comp Sci & Engn Bhubaneswar India Siksha O Anusandhan Dept Elect & Elect Engn Bhubaneswar India Siksha O Anusandhan Dept Comp Applicat Bhubaneswar India

ISBN: (纸本)9781538684313

As of late, deep learning has gained remarkable growth in various fields, for example, computer vision and natural language processing. Contrasted with conventional machine learning strategies, deep learning has a robust learning capacity and can improve utilization of datasets for feature extraction. In view of its practicability, deep learning turns out to be increasingly mainstream for many researchers to do research works. In this paper we mainly focus on the optimization of different parameters of convolutional neural network of deep learning for classifying 8000 labelled natural images of cat and dog. First the convolutional neural network is trained to learn features then ANN binary classifier is used for classification. Various level of optimization have been done to improve the performance level of the network and finally, we achieved the best classification accuracy of 88.31%.

关键词： deep learning machine learning neural network convolutional neural network

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Object recognition in images using convolutional neural network 2

Object recognition in images using convolutional neural netw...

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2nd international conference on Inventive Systems and Control, ICISC 2018

作者： Sudharshan, Duth P. Raj, Swathi Dept. of Computer Science Amrita School of Arts and Sciences Amrita Vishwa Vidyapeetham Mysuru Karanataka India

ISBN: (数字)9781538608074

ISBN: (纸本)9781538608074

Object detection from repository of images is challenging task in the area of computer vision and image processing in this work we present object classification and detection using cifar-10 data set with intended classification and detection of airplain images. So we used convolutional neural network on keras with tensorflow support the experimental results shows the time required to train, test and create the model in limited computing system. We train the system with 60,000 images with 25 epochs each epoch is taking 722to760 seconds in training step on tensorflow cpu system. At the end of 25 epochs the training accuracy is 96 percentage and the system can recognition input images based on train model and the output is respective label of images. © 2018 IEEE.

关键词： Deep neural networks

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Multi-modal hand gesture designing in multi-screen touchable teaching system for human-computer interaction 18

Multi-modal hand gesture designing in multi-screen touchable...

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2nd international conference on Advances in image processing (ICAIP) / 2nd international conference on Software Engineering and Development (ICSED

作者： Liu, Tingting Chen, Zengzhao Liu, Hai Zhang, Zhaoli Chen, Yingying Cent China Normal Univ Natl Engn Res Ctr E Learning Wuhan Peoples R China Carnegie Mellon Univ Sch Comp Sci 5000 Forbes Ave Pittsburgh PA 15213 USA City Univ Hong Kong Dept Mech Engn Hong Kong Peoples R China

ISBN: (纸本)9781450364607

In this paper, we developed a hand gesture recognition technology in a human-computer interaction system with several hand gestures. The proposed system can help teacher to control the multi-screen touchable teaching tools, such as sweeping right or left to access the previous or next slide, with a fist to call the eraser tool to rub out the wrong content. To verify its efficiency and other qualities, we conducted a quasi-experiment in our program site in east part of China which analyzed the pre- and post-test scores in Math class of each experimental groups. Moreover, the error recognition rate is reduced by increasing the relevant features and threshold training for the teaching application. Experimental results demonstrate that the proposed system achieves the high accuracy and real-time performance.

关键词： Human-computer interaction system development hand gesture recognition Educational technology

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Effective denoising with non-local means filter for reliable unwrapping of digital holographic interferometric fringes 1

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

作者： Aparna, P.L. Waghmare, Rahul G. Mishra, Deepak Sai Subrahmanyam Gorthi, R.K. National Institute of Technology Surathkal575025 India Indian Institute of Space Science and Technology Trivandrum695547 India Indian Institute of Technology Tirupati517506 India

ISBN: (数字)9789811078958

ISBN: (纸本)9789811078941

Estimation of phase from the complex interference field has become an emerging area of research for last few decades. The phase values obtained by using arctan function are limited to the interval (-π, π]. Such phase map is known as wrapped phase. The unwrapping process, which produces continuous phase map from the wrapped phase, becomes tedious in presence of noise. In this paper, we propose a preprocessing technique that removes the noise from the interference field, thereby improving the performance of naive unwrapping algorithms. For de-noising of the complex field, real part and imaginary parts of the field are processed separately. Real-valued images (real and imaginary parts) are processed using non-local means filter with non-Euclidian distance measure. The de-noised real and imaginary parts are then combined to form a clean interference field. MATLAB’s unwrap function is used as unwrapping algorithm to get the continuous phase from the cleaned interference field. Comparison with the Frost’s filter validates the applicability of proposed approach for processing the noisy interference field. © 2018, Springer Nature Singapore Pte Ltd.

关键词： image denoising

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ROBUST DWT-SVD BASED BLInd WATERMARKING FOR DIBR 3D VIDEO 2

ROBUST DWT-SVD BASED BLIND WATERMARKING FOR DIBR 3D VIDEO

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2nd international conference on computer, Communication, and Signal processing (ICCCSP) - Special Focus on Technology and Innovation for Smart Environment

作者： Vidya, K. Sujithra, T. Anna Univ Coll Engn Dept IST Madras 25 Tamil Nadu India

ISBN: (纸本)9781538611418

Watermarking has been supplicate as a tool for the preservation of cognitive property rights of multimedia contents. Because of their digital nature, multimedia documents can be mimeographed, reformed, metamorphosed, and promulgated very effortlessly. In this ambience, it is indispensable to burgeon a system for copyright protection, preservation against mimeograph, and validation of contents. In this case, a watermark data is embedded into the actual multimedia content in such a way that it is long-lasting to the content itself. Later on, such watermark can be extracted to manifest ownership to pursue the distribution of the patent toil through the network. In this developed watermarking, predominantly concentrated on Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). Apart from this, it also prevents the copyright of virtual views which is generated by using a technique called Depth-image-Based-Rendering. In this approach, secret data is inserted in the actual center vision using two mathematical transform, DWT and SVD. Then, multiple vision are automatically produced from the watermarked middle view and their corresponding profundity map at the content provider side. Finally watermark will be able to removed from all the three views in a sightless vogue without using the actual content of all the three views. In this proposed watermarking strategy is much better strong to image compression, noise addition and geometric distortion.

关键词： 3D video blind watermarking depth-image-based-rendering (DIBR) discrete wavelet transform (DWT) singular value decomposition (SVD)

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Fast and accurate 3D reconstruction based on grating projection 2

Fast and accurate 3D reconstruction based on grating project...

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2nd international conference on Mechanical, Electric and Industrial Engineering, MEIE 2019

作者： Ou, Ji Yang, Haima Liu, Jin Xie, Mengtao Xu, Wei School of Optical-electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China School of Electrical and Electronic Engineering Shanghai University of Engineering Science Shanghai China Suzhou Baizhu Hearing Technology Co. LTD Suzhou China

The principle model and calibration method of measurement are very important to the measurement system. In the vision measurement system, the auxiliary light source, such as laser, interference light, sine grating and so on, is usually needed in order to achieve high precision measurement results. In the existing 3D measurement methods for the surface topography of complex objects, in order to complete the measurement of absolute phase, it is usually necessary to process at least 6 fringe images, which limits the measurement speed. A method for obtaining the 3D shape of an object by using four sinusoidal fringes is presented. The truncated phase of the sinusoidal fringe is obtained by using the four-step phase shift. When the fringe order is obtained, the time of data processing can be reduced and the measurement speed can be further improved. The reconstruction time is less than two minutes and the maximum absolute error and maximum RMS error are 0.033mm and 0.029mm respectively when the height of the face model is 45mm. The validity and practicability of the method are verified, and it has a wide application prospect in high-speed and real-time 3D measurement of complex topography. © 2019 IOP Publishing Ltd.

关键词： Light sources

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Automatic Recognition for Arbitrarily Tilted License Plate 18

Automatic Recognition for Arbitrarily Tilted License Plate

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2nd international conference on Video and image processing (Icvip)

作者： Lu, Nanxue Yang, Wei Meng, Ajin Xu, Zhenbo Huang, Huan Huang, Liusheng Univ Sci & Technol China Hefei Anhui Peoples R China Xingtai Financial Holdings Grp Co Ltd Hefei Anhui Peoples R China

ISBN: (纸本)9781450366137

In this paper, we propose a novel automatic license plate recognition (ALPR) method based on convolutional neural network to achieve a better performance in detecting and recognizing license plate (LP) with relatively large angle of inclination. Most existing methods only perform well on dataset where LPs are presented in almost upright position with little or no tilted angle. While, in practice, the LP images collected by roadside cameras or hand-held image capturing devices can be fairly slanted, which causes great difficulties on recognition tasks. To solve this problem, we design an angle correction module and integrate it into a holistic ALPR model with a spatial transformer network embedded inside. The whole model can be trained end-to- end by back-propagation. A large and comprehensive rotated LP dataset Rlpd is collected and introduced in our work for model training and testing. Through extensive experiments, this approach is proved to have a better performance on tilted license plate dataset in terms of accuracy and computational cost than other state-of-the-art methods.

关键词： Car License Plate Detection and Recognition Intelligent Transportation System computer vision Convolutional Neural Network

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Analysis of TFT-LCD Point Defect Detection System Based on Machine vision

Analysis of TFT-LCD Point Defect Detection System Based on M...

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2019 2nd international conference on computer Science and Advanced Materials(CSAM 2019)

作者： Zhang Wenqian Zhang Jinhong Department of Computer Science and Technology the University of Electronic Science and Technology of China College of Materials and Energy the University of Electronic Science and Technology of China

This paper mainly gives an introduction to the machine vision-based TFT-LCD point defect detection control system. As the use of otsu algorithm for segmentation is not good enough for TFT-LCD image in the condition of weak contrast ratio of the object and background, it is proposed to improve the threshold and extract function by Wible function, and the optimized otsu algorithm has better segmentation effect than the traditional otsu algorithm in the condition of weak contrast ratio of the object and background. After the testing by transplanting the Matlab image processing program to the hardware platform of TFT-LCD defect detection control system, the experimental results show that the detection control system can quickly and accurately process three types of defects, and the shortest detection time can be shortened to 4.5 s.

关键词： machine vision TFT-LCD otsu algorithm defect detection

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