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Computer Science Society (SCCC) International conference Chilean FLAGGED

作者： Eric Orellana-Romero Javier SanMartin-Hernandez Cristian Duran-Faundez Vincent Lecuire Cristhian Aguilera Departamento de Ingeniería Eléctrica y Electrónica Facultad de Ingeniería Universidad del Bío-Bío Concepcion Chile Centre de Recherche en Automatique de Nancy (CRAN) CNRS Université de Lorraine Vandoeuvre-les-Nancy France

In this paper we present Sim-LIT, a framework for the simulation of packet loss effects on the quality of non-coded or coded still images transported over wireless sensor networks. The tool is focused on image quality assessment and it can be used to evaluate error resilience during image communications. In this first version the evaluation of block interleaving methods is provided. Sim-LIT is highly configurable, providing several options and additional tools. It may be useful to rapidly evaluate interleaving algorithms, or other techniques, or to perform extensive tests considering various image files and loss patterns. Through different simulations we demonstrate the potential of Sim-LIT as a tool for supporting research activities on the image processing and wireless sensor networks domains.

关键词： image reconstruction Wireless sensor networks PSNR image communication Adaptation models

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image Forgery Detection Using Hybrid Model

Image Forgery Detection Using Hybrid Model

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Intelligent Signal processing and Effective Communication Technologies (INSPECT), IEEE International conference on

作者： Priya Metri Sakshi Balla Shreya Pawar Atharva Sharma Prashant Sakunde Artificial Intelligence and Data Science Dr. D. Y. Patil Institute of Technology Pimpri Pune India

ISBN: (数字)9798350379525

ISBN: (纸本)9798350379532

The growing demand for trustworthy picture forgery detection techniques to maintain the integrity of visual content across a range of applications is addressed in this work. To improve picture authentication accuracy and efficiency, a user-friendly cascaded framework combining Support Vector Machines (SVM) and VGG 16 is presented. First, a highly effective supervised learning system called Support Vector Machines (SVM) rapidly filters photos by identifying overt alteration indi-cators. After passing this phase, images are examined and refined even more with the help of the VGG 16 deep learning model. When SVM and VGG16 are combined, their complimentary strengths are utilised, which improves accuracy and speeds up identification when compared to other approaches. According to benchmark datasets, the proposed method outperforms earlier methods with respect to accuracy and computational efficiency. This strategy may benefit many real-world applications- based on forensic verification, verification of media integrity, medical image authentication, and intellectual property protection-in the here-and-now solutions. This work enhances the confidence and trustworthiness of digital communications by providing an efficient, friendly user tool for the verification of visual content.

关键词： Support vector machines visualization Accuracy Filters Forensics Supervised learning Authentication Intellectual property Media Forgery

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C22. Enhanced fusion for Infrared and visible images

C22. Enhanced fusion for Infrared and visible images

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National conference on Radio Science (NSRC)

作者： R. F. Soliman M. Amin F. E. Abd El-Samie Mathematics Department Faculty of Science Menoufia University Shibin El Kom Egypt Department of Electronics and Electrical Communications. Faculty of Electronic Engineering Menoufia University Menouf Egypt

An enhanced fusion technique for Infrared (IR) and visible images, which is based on the curvelet transform and homomorphic processing using the additive wavelet transform, is presented in this paper. The idea behind this technique is based on fusing the IR and visible images using the curvelet transform, and then decomposing the fused image into sub-bands in an additive fashion using the additive wavelet transform. The homomorphic enhancement is performed on each sub-band, separately. Finally, an inverse additive wavelet transform is performed on the homomorphic enhanced sub-bands to get an enhanced fused image with better visual details. The simulation results with real IR and visible images show that the proposed technique effectively enhances IR targets and preserves the details of visible images.

关键词： image fusion Discrete wavelet transforms Additives Educational institutions image edge detection

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Underwater image Enhancement with a Total Generalized Variation Illumination Prior

Underwater Image Enhancement with a Total Generalized Variat...

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IEEE International conference on Big Data and Cloud Computing (BdCloud)

作者： Zhengjie Zhao Yuxiang Dai Peixian Zhuang School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

In order to promote the visual quality of degraded underwater images, we develop an innovative variational model based on Retinex with a total generalized variation (TGV) prior on the illumination. The TGV prior is adopted to approximate piecewise smoothness and piecewise linear smoothness of the illumination, which combines the first-order and second-order total variation (TV) to model the variation of illumination. When adopting this illumination prior in the Retinex-based algorithm, the illumination and reflection are well separated, and underwater enhanced results appear more natural and their details and edges are better preserved. Then an efficient iterative optimization method is derived to settle the proposed model via alternately calculating the illumination and the reflection simultaneously. Numerous experiments on both visual results and objective metrics demonstrate the superiority of our method compared with several underwater enhancement methods. In addition, the proposed method can be extended for dehazing, sandstorm removal and low illumination image enhancement, which can illustrate better capacity of our model.

关键词： Lighting image color analysis Mathematical model Optimization image enhancement visualization Adaptation models

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Design of Optimized Neuro-Wavelet Based Hybrid Model for image Compression

Communications in Computer and Information Science

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communications in Computer and Information Science 2011年 205 M4D卷 96-107页

作者： Gambhir, Deepak Rajpal, Navin Singh, Vipula ECE Amity School of Engineering and Technology Bijwasan New Delhi India USIT Guru Gobind Singh Inderprastha University Dwarka New Delhi India ECE RNS Institute of Technology Bangalore India

ISBN: (纸本)9783642240546

images are in its standard canonical form for a matrix have significant amount of redundant data. Thus image compression methods always under wide attention for efficient multimedia data transmission and storage. This paper concerned with the design of an optimized hybrid Neuro-Wavelet based model for image compression. In this design first the images are decomposed to various sub-band via wavelet transform and then they are fed to different supervised Neural Networks which are optimized with Linear Programming. The simulation results show the clear improvement over the existing methods objectively by PSNR and subjectively by visual appearance. © Springer-Verlag Berlin Heidelberg 2011.

关键词： image compression

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Multi-instance local exemplar comparisons for pedestrian detection

Multi-instance local exemplar comparisons for pedestrian det...

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IEEE International conference on Signal processing, communications and Computing (ICSPCC)

作者： Chensheng Sun Sanyuan Zhao Jiwei Hu Kin-Man Lam Center for Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hung Hom Hong Kong China School of Computer Science and Technology Beijing Institute of Technology Beijing China

We propose to use the partial similarity between a sample and a number of exemplars as the image features for visual object detection. Define a part of the object as a sub-window inside the object bounding box, for each part of the object, a codebook of local appearance templates is learned. By using multiple templates for each part, and allowing the template to be compared with a bag of part instances in the neighborhood of the canonical location, the deformable and multi-aspect properties can be captured. A linear classifier is learned with feature selection, selecting a subset of the templates. To improve the efficiency of the detector, a rejection cascade is built by calibrating the linear classifier; the rejection cascade makes decisions using partial scores. Experimental results show that our method substantially improves the performance for human detection.

关键词： Feature extraction Support vector machines Detectors Training Kernel Object detection visualization

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Global Gabor features for rotation invariant object classification

Global Gabor features for rotation invariant object classifi...

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IEEE International conference on Intelligent Computer Communication and processing (ICCP)

作者： Ioan Buciu Ioan Nafornita Ioannis Pitas Electronics Department Faculty of Electrical Engineering and Information Technology University of Oradea Romania Electronics and Communications Faculty Politehnica University of Timisoara Timisoara Romania Department of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9781424426737

The human visual system can rapidly and accurately recognize a large number of various objects in cluttered scenes under widely varying and difficult viewing conditions, such as illuminations changing, occlusion, scaling or rotation. One of the state-of-the-art feature extraction techniques used in image recognition and processing is based on the Gabor wavelet model. This paper deals with the application of the aforementioned model for object classification task with respect to the rotation issue. Three training sample sizes were applied to assess the methodpsilas performance. Experiments ran on the COIL-100 database show the robustness of the Gabor approach when globally applied to extract relevant discriminative features. The method out-performs other state-of-the-art techniques compared in the paper such as, principal component analysis (PCA) or linear discriminant analysis (LDA).

关键词： Gabor filters Feature extraction Training Principal component analysis Databases Object recognition Robustness

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A Mixed Appearance-based and Coding Distortion-based CNN Fusion Approach for In-loop Filtering in Video Coding

A Mixed Appearance-based and Coding Distortion-based CNN Fus...

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IEEE visual communications and image processing (VCIP)

作者： Jian Yue Yanbo Gao Shuai Li Menghu Jia School of Information & Comunication Engineering University of Electronoc Science & Technology of China Chengdu China School of Software Shandong University Jinan China School of Control Science and Engineering Shandong University Jinan China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

With the success of the convolutional neural networks (CNNs) in image denoising and other computer vision tasks, CNNs have been investigated for in-loop filtering in video coding. Many existing methods directly use CNNs as powerful tools for filtering without much analysis on its effect. Considering the in-loop filters process the reconstructed video frames produced from a fixed line of video coding operations, the coding distortion in the reconstructed frames may share similar properties that can be learned by CNNs in addition to being a noisy image. Therefore, in this paper, we first categorize the CNN based filtering into two types of processes: appearance-based CNN filtering and coding distortion-based CNN filtering, and develop a two-stream CNN fusion framework accordingly. In the appearance-based CNN filtering, a CNN processes the reconstructed frame as a distorted image and extracts the global appearance information to restore the original image. In order to extract the global information, a CNN with pooling is used first to increase the receptive field and up-sampling is added in the late stage to produce pixel-level frame information. On the contrary, in the coding distortion-based filtering, a CNN processes the reconstructed frame as blocks with certain types of distortions by focusing on the local information to learn the coding distortion resulted by the fixed video coding pipeline. Finally, the appearance-based filtering stream and the coding distortion-based filtering stream are fused together to combine the two aspects of CNN filtering, and also the global and local information. To further reduce the complexity, the similar initial and last convolutional layers are shared over two streams to generate a mixed CNN. Experiments demonstrate that the proposed method achieves better performance than the existing CNN-based filtering methods, with 11.26% BD-rate saving under the All Intra configuration.

关键词： Distortion Feature extraction image reconstruction Encoding Convolutional codes image restoration Deep learning

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Machine Vision-based Tool Location and Wear Monitoring in Micro turning: Optical Setup and image processing Approaches

Machine Vision-based Tool Location and Wear Monitoring in Mi...

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Innovations in communications, Electrical and Computer Engineering (ICICEC), International conference on

作者： Shalupriya M K.P. Indira Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Nanobiomaterials Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India

ISBN: (数字)9798350376517

ISBN: (纸本)9798350376524

In micro turning, tool placement, wear, and breakage are crucial as they affect precision and surface finish. Flank wear is problematic since it impacts dimensional accuracy, and current methods that rely on CNC encoder inputs and radius compensation are insufficient for micro turning due to the small tool sizes involved. Detecting flank wear in micro turning is difficult as the tools are often too small for visual inspection, making monitoring at micron levels a challenge. This research investigates using machine vision to monitor tool position and flank wear in micro turning. The optical system, comprising a 12X super zoom lens and 3MP CMOS image sensor, is assessed alongside three lighting techniques: direct, indirect, and backlighting. Preliminary image analysis, using Gaussian filters and histogram equalization, indicates lighting's importance. Early results, comparing new and worn tools using exclusive operators, are promising, but further image enhancements are necessary for accurate classification and wear detection.

关键词： Optical filters Integrated optics visualization Technological innovation Accuracy Lighting Turning Optical imaging Optical sensors Monitoring

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House Hold Guide Using Augmented Reality

House Hold Guide Using Augmented Reality

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International conference on communications and Signal processing

作者： S. Venkata Siva Prasanth A. Sriram Kommireddy Akhila SRM Institute of Science and Technology Kancheepuram district Tamil Nadu

Human work produces desired output but we wondered how can a computer understand human thoughts and actions a few years ago. But, in no time, our dream is put in action. Virtual animations and presentations have taken over the traditional man made works. Augmented reality is one such kind in which an image is read and a computer generated replica is displayed. Augmented reality is the technology that superimposes a computer-generated image on a user's view of the real world, thus providing a conventional view. It has its own advantages in various fields like Medicine, Engineering and Science. In the fields of engineering, image processing can be used to improve images in visual courses like tutorials for automation where imagining the working of an automated device is difficult. The same concept can be applied on for house hold devices. House hold devices may develop some technical issues due to wear and tear and need immediate attention. A technician might not be available always at that moment. But, the house hold guide would no longer let you wait until help arrives. It will teach you the whole procedure on how to fix the problem step by step. It requires a portable CPU and a display. Since this device is product oriented, the procedure of fixing any house hold equipment has to be first fed into the device and then can be used at some time later. After the device is taught with the procedure, it will guide the user when he comes across the problem while using that device. For instance, installing a table fan can be taught to any person who has no prior knowledge about it using this house hold guide. In this way, a house hold guide can help every person in all the troublesome equipment in his/her house.

关键词： Augmented reality image processing Three-dimensional displays Transforms Software Cameras Lighting

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