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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems III"

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Objective Quality Assessments of Restoration images

Objective Quality Assessments of Restoration Images

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International conference on Communication on Networks (COMNET)

作者： Kamireddy, Rasool Reddy Punem, Shivaramakrishna Jangala, Supriya Chamarthi, Geetha Ramakrishna Dutt Srinivas, Kota Yedukondalu Malla Reddy Inst Technol & Sci Secunderabad India

ISBN: (纸本)9789811027505;9789811027499

Picture (image) restoration is one of the significant concerns in the domain of image processing. It aims to recover the original picture (image) from its degraded observed image. After restoration, quality is another important task. A handful of various quality assessment approaches are used to evaluate the quality of a restored images, among them objective quality assessments is the best leading approach compared to others. Here our proposal mainly focuses on the analysis of restored images using several techniques of objective fidelity criteria. From simulation results we can easily examine the performance of different image restoration algorithms under different restored objects.

关键词： image restoration Degradation model image quality Quality assessments Objective fidelity criteria

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image Encryption in Code Based Compression algorithms Based on Multilevel image Structure Model 9

Image Encryption in Code Based Compression Algorithms Based ...

引用

9th International Congress on Ultra Modern Telecommunications and Control systems (ICUMT)

作者： Bezzateev, Sergey Voloshina, Natalia ITMO Univ St Petersburg Univ Aerosp Instrumentat St Petersburg Russia

ISBN: (纸本)9781538634356

image compression is a widely adopted technique used for effective image storage and transmission over open communication channels in cyber-physical systems. Standard cryptographic algorithms are usually used to reach this goal. Therefore, in order to organize effective and secure storage of images it is required to follow two independent and sequential procedures compression and encryption. In the scenario of interest, it is needed to do compression and encryption transformations in reverse order to restore the original image, i.e. it is necessary to have a so-called "code book" similarly as for encryption and decryption to have a secret key. An effective way of combining these procedures for digital images is proposed in this manuscript. This research is mainly focused on the compression methods that consider significance of the initial multimedia object (for example image) different parts to increase the quality of resulting (decompressed) image. One of the most effective approaches for this task is to utilize error-correcting codes (FCC) that allow to limit the number of resulting errors (distortion) as well as to ensure the value of resulting compression ratio. Application of such codes enable to distribute errors that are added during the processing procedure according to predefined significance of the initial multimedia object elements. The approach that is based on weighted Hamming metric that makes it possible to guaranty the limitation of maximum error number (distortions) that takes into consideration predefined significance of the image zones is represented as an example. The way to use subclass of Goppa codes perfect in weighted Ilamming metric when Goppa polynomials are used as a secret key is presented as well. The additional effect of such encrypted compression methods is auto-watermarking of the resulting image.

关键词： image coding Distortion Measurement Error correction codes Encryption Decoding Communication channels

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A Seeded Fuzzy C-Means Based Approach to Automatic Cup-to-Disc Ratio Measurement

A Seeded Fuzzy C-Means Based Approach to Automatic Cup-to-Di...

引用

IEEE International conference on systems, Man, and Cybernetics (SMC)

作者： Santos, Luis Veras, Rodrigo Rabelo, Ricardo Aires, Kelson Aires, Olivan Univ Fed Piaui Dept Computat Teresina Piaui Brazil

ISBN: (纸本)9781538616451

Glaucoma is an eye disease that causes irreversible vision loss. Retinography is done manually by the ophthalmologist and is the cheapest, least invasive and most effective way to diagnose glaucoma. The ratio between the diameter of the outer part of the Optic Disc (OD) and the cup (internal part) called CDR (cup-to-disc ratio) is an important indicator of glaucoma presence in patients. This paper proposes a semi-automatic approach that includes the segmentation of OD and cup regions. The proposed approach consists of four stages. The first stage consists of preprocessing the retinal image, in order to remove blood vessels and a possible influence in the segmentation stage. In the second stage we apply the Seeded Fuzzy C-means algorithm to segment the preprocessed image in order to indentify cup and OD. The third step involves the application of a post-processing so that non-segmented regions are filled. Finally, the last step calculates the value of the CDR associated with the retinal image. To verify the applicability of the proposed approach, we carried out tests in two public image databases: DRISHTI-GS and RIM-ONE r3. The results obtained illustrate the feasibility of applying the approach in order to effectively assist ophthalmologists in the segmentation of cup and OD, as well as the calculation of the CDR.

关键词： image segmentation Biomedical imaging Blood vessels Clustering algorithms Retina Morphological operations

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Eye Fatigue Detection System

Eye Fatigue Detection System

引用

International conference on System Modeling & Advancement in Research Trends (SMART)

作者： Ch. Sravan K.J. Onesim V. Sri Sai Bhavana R. Arthi G. Srinadh Department of ECE VBIT Hyderabad India

ISBN: (纸本)9781538663707

Now a day's many accidents occur due to Driver Fatigueness. The proposed system notices the Eye fatigue using image processing by calculating the threshold values at specific location. This system works on auditing eyes and face of the driver. Person is said to be fatigue if his/her eyes are closed for a certain span of time and notifies. The proposed system mainly concentrates on eyes region. The main aim is to protect the driver without occurring of any accident by alerting the driver. Therefore, this system proves to be best for detection of Eye Fatigue compared to other systems which are made up of microprocessors. With this system, major road accidents occur due to driver fatigue can be evaded.

关键词： Fatigue Vehicles image color analysis Accidents Classification algorithms Face

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Underwater Dynamic Target Tracking of Autonomous Underwater Vehicle Based on MPC Algorithm

Underwater Dynamic Target Tracking of Autonomous Underwater ...

引用

IEEE International conference on Underwater System Technology: Theory and Applications (USYS)

作者： Yali Wei Daqi Zhu Zhenzhong Chu Laboratory of Underwater Vehicles and Intelligent Systems Shanghai Maritime University

ISBN: (纸本)9781538694060

In this paper, a dynamic target tracking method based on model predictive control (MPC) algorithm was proposed for autonomous underwater vehicle (AUV). Through the processing of AUV sonar images, the dynamic target can be identified and located in real time. Then the Kalman filter was used to reasonably predict the position of the dynamic target at the next moment. Finally, MPC algorithm is applied to track the dynamic target online and follow it. Through experiments, the actual position of the target was obtained. And by simulation, MPC can accurately track dynamic targets, which has also been proved. This algorithm can not only track the trajectory, but also track the dynamic target, which meets the practical requirements.

关键词： Target tracking Sonar Heuristic algorithms Kalman filters Vehicle dynamics Mathematical model image processing

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Real-Time High-Quality Specular Highlight Removal Using Efficient Pixel Clustering

Real-Time High-Quality Specular Highlight Removal Using Effi...

引用

Brazilian Symposium on Computer Graphics and image processing (SIBGRAPI)

作者： Antonio C.S. Souza Márcio C.F. Macedo Verônica P. Nascimento Bruno S. Oliveira Dept. of Comput. Sci. Fed. Inst. of Bahia Salvador Brazil Universidade Federal da Bahia Salvador BA BR Computaçáo Brasil Salvador BA Brazil

On the basis of the dichromatic reflection model, recent specular highlight removal techniques typically estimate and cluster illumination chromaticity values to separate diffuse and specular reflection components from a single image. While these techniques are able to obtain visually pleasing results, their clustering algorithms suffer from bad initialization or are too costly to be computed in real time. In this paper, we propose a high-quality pixel clustering approach that allows the removal of specular highlights from a single image in real time. We follow previous work and estimate the minimum and maximum chromaticity values for every pixel. Then, we analyze the distribution pattern of those values in a minimum-maximum chromaticity space to propose an efficient pixel clustering approach. Afterwards, we estimate an intensity ratio for each cluster in order to separate diffuse and specular components. Finally, we present optimization strategies to implement our approach efficiently for both CPU and GPU architectures. Experimental results evaluated in the available dataset show that the proposed approach is not only more accurate, but is also two times faster than the state-of-the-art when running solely on the CPU. Running on the GPU, we show that our approach requires ≈24 milliseconds to remove specular highlights in an image with 3840×2160 (4k) resolution. That makes our GPU implementation more than one order of magnitude (20×) faster than the state-of-the-art for 4k resolution images, while providing the desired effect accurately.

关键词： Real-time systems Clustering algorithms image color analysis Graphics processing units Task analysis Optimization image resolution

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Robust image Denoising and Smoothing with Generalised Spatial-Tonal Averages

Robust Image Denoising and Smoothing with Generalised Spatia...

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IEEE International conference on Fuzzy systems (FUZZ-IEEE)

作者： Wilkin, Tim Beliakov, Gleb Deakin Univ Sch Informat Technol 221 Burwood Hwy Geelong Vic 3125 Australia

ISBN: (纸本)9781509060344

This article investigates image filtering and smoothing from the perspective of a recent generalisation of the notion of aggregation functions in fuzzy systems, called pre-aggregation functions. Mixture functions describing a broad class of robust spatial-tonal filters and smoothers are derived using penalty-based methods. Several existing filters are re-derived using this approach and several novel filters are proposed, which are able to better handle filtering in contexts where the pixel to be filtered is itself an outlier in the local neighbourhood. The proposed class of Robust Bilateral Filters formalises and generalises a recent result of Chaudhury, who noted that using a filtered version of an image to compute tonal weights for a Bilateral Filter gave more robust denoising. Filter performance is validated using standard test images and quantified using peak signal-to-noise ratio and visual similarity, finding novel filters that exceed the performance of the standard Bilateral Filter.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Fully automated CADx for early breast cancer detection using image processing and machine learning

Fully automated CADx for early breast cancer detection using...

引用

International conference on Microelectronics, ICM

作者： Monica Ezzat Gamil Mariam Mohamed Fouad Mohamed A. Abd El Ghany Klaus Hoffinan Electronics Engineering Dept German University in Cairo Cairo Egypt Integrated Electronic Systems Lab TU Darmstadt Germany

ISBN: (纸本)9781538681688;9781538681671

Breast cancer accounts for 16% of all cancers among females. Current early detection methods are expensive or computationally complex and thus unsuitable for developing countries. For this reason, a real-time fully automated Computer Aided Diagnosis system for Breast Cancer early detection from Ultrasound images is built in this paper. The proposed and implemented design comprises into its modules state of the art techniques and methods. The implemented design includes preprocessing/filtering of the input ultrasound image, segmentation of the region of interest from the background image and feature set calculation/extraction. Machine learning algorithms were implemented for classification of the tumour. Successful implementation with satisfactory run time is achieved with a final accuracy improved by 10% from previous work using the same set of features. Additional evaluation metrics like precision-recall plots and confusion matrices were also used to test and evaluate the system overall balanced performance.

关键词： Feature extraction Tumors Breast cancer Ultrasonic imaging image segmentation

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The Application of One-Class Classifier Based on CNN in image Defect Detection

The Application of One-Class Classifier Based on CNN in Imag...

引用

Complex Adaptive systems conference on Engineering Cyber Physical systems (CAS)

作者： Zhang, Mei Wu, Jinglan Lin, Huifeng Yuan, Peng Song, Yanan South China Univ Technol Sch Automat Guangzhou 510640 Guangdong Peoples R China Guangdong Univ Technol Coll Automat Guangzhou 510006 Guangdong Peoples R China

In the field of defect detection, image processing algorithms and feature extraction algorithms have some limitations, owing to their necessity for extracting a large number of different features of diverse products images. Meanwhile, the images of defective products are less and various. Aiming at these problems, we presented a One-Class classifier based on deep convolution neural network to detect the defect images in this paper. We design a loss function with the penalty term based on Euclidean distance to train the deep convolution neural network model. A hypersphere is used as classification decision surface after setting an appropriate hypersphere radius according to the inspection accuracy. It maps the non-defective products into a hypersphere in a high dimensional feature space, while the defect images are mapped somewhere far from the center of hypersphere. Thus, a One-Class classifier based on convolutional neural network(CNN) model is proposed to detect the defects. Experiments show that the proposed method, with less number of iteration, help build the classifier for image defect detection with high generalization ability and high detection precision. (C) 2017 The Authors. Published by Elsevier B.V.

关键词： One-Class classifier CNN image defect detection Hypersphere

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Object detection algorithm for segregating similar coloured objects and database formation

Object detection algorithm for segregating similar coloured ...

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IEEE International conference on Circuit ,Power and Computing Technologies (ICCPCT)

作者： Alexander, Anusha Dharmana, Meher Madhu Amrita Univ Amritapuri Amrita Vishwa Vidyapeetham Amrita Sch Engn Dept Elect & Elect Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9781509049677

Recent advancement in the processing power of on-board computers has encouraged engineers to impart visual feedbacks into various systems like mechatronics and internet of things. Applications ranging from CCTV surveillance to target detection and tracking using UAVs, there is a wide variety of demand on image processing techniques in terms of computational time and quality. In this scenario, developing generalised algorithms which gives a freedom to user in choosing the trade-off between quality and quick response is a challenging task. In this paper a novel boundary detection algorithm for segregating similar coloured objects in an image is presented, which accommodates a degree of freedom in choosing resolution of object detection to the detection time. This method uses colour based segmentation as preprocessing technique to reduce overall computational complexity. It is independent of the shape (convex or non-convex) and size of the object. Algorithm is developed using Open-CV libraries and implemented for separating similar coloured vehicles from an image of different vehicles on road. Implementation results showing different choices of boundary tightness and computation times are showcased.

关键词： Boundary detection Corner detection image processing Splitting images Database formation

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