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International conference on Advances in ICT for Emerging Regions

作者： Bandarage Shehani Sanketha Rathnayake Lochandaka Ranathunga Department of Information Technology University of Moratuwa Katubedda.Moratuwa Sri Lanka

ISBN: (纸本)9781538673539;9781538673522

Lane detection and tracking is essential concern in vision based autonomous vehicle navigation. this paper proposes a novel method based on probabilistic Hough transform and motion vector based analysis for detecting and tracking lane and lane departures. It addresses drawbacks of current systems under hazy situations with learning method based on previous tracking records of the system. In this method relevant lane mark features are extracted based on color variations. therefore used HSL color model which gives higher color contrast of road surface and the markings. In order to reduce computation, processing algorithms are applied only to the region of interest (ROI). Edges of the selected regions are extracted with Canny Edge Detection. Since lane markings are made with set of straight lines, straight lines are extracted with Probabilistic Hough Transform. Extracted lines are analyzed to detect lane. To monitor lane departures vehicle's motion is detected and tracked based on motion vector analysis with Lucas Kanade Optical Flow algorithm. Previous detection records are used to track the lane continuously in hazy situations and provide prediction on approximate lane for the roads without lane markings. Experiments were performed on set of videos taken from vehicles' front camera mounted on dashboard. According to the experiments the proposed algorithm has 81.9% of sensitivity in lane detection and 63.5% in approximate lane predictions for the roads without lane markings. Lane detection algorithm has 83% precision, 68% recall and 0.75 F1 score with threshold brightness value 140. Algorithm can further improved to guide the autonomous vehicles to take accurate decisions on selecting safety lane to drive ahead in different situations.

关键词： Feature extraction Roads image color analysis Prediction algorithms Tracking image edge detection Transforms

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Improving the Partial Product Tree Compression on Signed Radix-2m Parallel Multipliers

Improving the Partial Product Tree Compression on Signed Rad...

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Annual IEEE Northeast Workshop on Circuits and systems (NEWCAS)

作者： Leandro M. G. Rocha Morgana Macedo Guilherme Paim Eduardo Costa Sergio Bampi Graduate Program in Microelectronics (PGMicro) - Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Graduate Program on Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9781728170442

ISBN: (纸本)9781728170459

Arithmetic operations are intrinsic to any embedded devices, and they usually have a significant impact on the circuit speed, area, and power consumption. Applications like video processing, digital signal processing, machine learning, among others, rely heavily on multipliers to execute their algorithms. Radix-2 m multipliers have been reported as one of the most power-efficient circuits. However, their architecture has not been explored nor optimized to improve the circuit quality. this work proposed two sign extension optimization techniques for these multipliers, aiming for better power efficiency and a smaller area. the baseline radix-4 (m=2) multiplier and its optimized versions were synthesized in a commercial 65nm technology to evaluate their performance. Results show that the optimized versions achieve power efficiency gains from 16.4% up to 78.6%, with circuit area reduction up to 49.2%.

关键词： Adders Optimization Power dissipation Computer architecture Digital signal processing Signal processing algorithms Standards

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Synthetic Ultra-Wideband Integrated Pulse Generator for Millimeter-Wave Imaging Applications

Synthetic Ultra-Wideband Integrated Pulse Generator for Mill...

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Annual IEEE Northeast Workshop on Circuits and systems (NEWCAS)

作者： Amir Mirbeik-Sabzevari Laleh Najafizadeh Negar Tavassolian Stevens Institute of Technology Hoboken NJ USA Rutgers University Piscataway NJ USA

ISBN: (数字)9781728170442

ISBN: (纸本)9781728170459

this work presents three integrated pulse generators that can collectively provide a synthetic ultra-wide imaging bandwidth of 100 GHz in the millimeter-wave regime. Such a development is the first step towards the realization of a fully-integrated ultra-high-resolution imaging chip for biomedical applications. the pulse generators are designed in a Global Foundry 130-nm SiGe BiCMOS process technology and produce pulses with frequency ranges of 10-40-GHz, 40-75-GHz, and 75-110-GHz respectively. the three sub-band pulse generators possess a similar differential pulsed VCO configuration with the highest average power consumption of 40 mW.

关键词： image reconstruction Scattering parameters Reconstruction algorithms Oscillators Transmitting antennas

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Effectiveness of Quantum Computing in image processing for Burr Detection 18th

Effectiveness of Quantum Computing in Image Processing for...

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Proceedings of the 18th International conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2023

作者： Merino-Bajo, Santiago Sánchez-González, Lidia Riego, Virginia Matellán, Vicente SCAYLE: Fundación Centro de Supercomputación de Castilla y León León Spain Departamento de Ingenierías Mecánica Informática y Aeroespacial Universidad de León León24071 Spain

ISBN: (纸本)9783031425288

Technology is developing at a dizzying pace to make our lives easier. Among other innovations, quantum computing, which is based on quantum mechanics, is evolving with the aim of solving all the problems that traditional computing is unable to solve. Quantum computing, unlike traditional computing, relies on qubits (quantum bits) that can be in superposition of the values 0 and 1, as well as other fundamentals, such as interference or entanglement. this paper analyses the use of quantum computing for image processing, testing the efficiency when quantum computers are employed. To do that, the Flexible Representation of Quantum images model of image representation is implemented in a quantum simulator to solve a particular problem. therefore, images of machined parts are processed in order to detect the edges of the mask what can determine the presence of burrs. Detecting burrs improves the surface finish and, in turn, the quality of industrial processes. the results of the proof of concept show that, although compared to traditional computing, quantum algorithms are not yet efficient enough to match or even surpass classical algorithms, they are promising. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computer vision

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A Heterogeneous Implementation of the Sobel Edge Detection Filter Using OpenCL

A Heterogeneous Implementation of the Sobel Edge Detection F...

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International conference on Modern Circuits and systems Technologies (MOCAST)

作者： theodora Sanida Argyrios Sideris Minas Dasygenis Department of Electrical & Computer Engineering University of Western Macedonia Kozani Greece

ISBN: (数字)9781728166872

ISBN: (纸本)9781728166889

Today, edge detection is a cornerstone technique as edges are essential in many applications, such as image processing and biometric imaging. One popular algorithm for edge detection is the Sobel. Many researchers have focused on accelerating the Sobel filtering, but to the best of our knowledge we are the first to propose a 5×5 convolution kernel implementation using OpenCL. In this work, we implement the Sobel filter, one of the most effective and popular edge detection algorithms in image processing, in the OpenCL programming language. From the implementation of the Sobel algorithm we compare the performance of the CPU and GPU through OpenCL, in typical images ranging from 64×64 to 4096×4096 pixels. the Sobel operator uses a pair of 3×3 horizontal and vertical convolution kernels for edge detection functions. We apply 3×3 and 5×5 convolution kernels using OpenCL and compare them. the results have shown that for all image sizes, the GPU speed up ranges from 11,18 to 15,46 times with 3×3 convolution kernels, while speed up is from 10,05 to 13,46 times for the 5×5 convolution kernels. Finally, the results of our implementation are compared to other existing implementations and found to achieve better performance.

关键词： Kernel Convolution image edge detection Graphics processing units image resolution Computer languages Computer architecture

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Fruit Sorting with Amplitude-only Measurements

Fruit Sorting with Amplitude-only Measurements

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European Radar conference (EURAD)

作者： F. Zidane J. Lanteri L. Brochier J. Marot C. Migliaccio Universit&#x00E9 C&#x00F4 te d&#x2019 Azur France Aix Marseille Universit&#x00E9 France

ISBN: (纸本)9781665447232

the food industry is in constant demand of performing and easy to implement Non-Destructive Evaluation NDE techniques. In this paper, we tackle the problem of the automatic inspection of fruits and more specifically, the sorting of healthy and damaged fruits, taking apples and peaches as examples. In a recent work, we have explained how to proceed by combining mm-Wave measurements processed with a 2D-FFT and Machine Learning algorithm. the accuracy reaches at least 80%. Although the 2D-FFT is a real-time processing and thus interesting for an industrial implementation, it requires complex measurements, i.e amplitude and phase, which makes the acquisition system more complex. Here we aim to overcome this difficulty by processing amplitude-only measurements. We make use of an image processing based on the direct conversion of the measured amplitude into images. the images form the dataset for the classifier that we choose as a non-linear SVM with a RBF kernel. the advantage of the SVM is that the computational burden is moved to the training phase where we compute the optimal hyper-parameters C* and ϒ*, while the test is very fast. First, we describe the complete workflow and use a set of apples measured in W-band in Autumn 2019 for validation purpose. We then extend the validation to measurements of peaches conducted over a long time period (summer 2019 and 2020). Finally, we investigate the robustness of the method over frequency while moving to the D-band. For all tests the accuracy is of 100%

关键词： Support vector machines Antenna measurements Training Millimeter wave measurements Radar antennas Time measurement Real-time systems

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A soft kinetic data structure for lesion border detection

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BIOINFORMATICS 2010年第12期26卷 i21-i28页

作者： Kockara, Sinan Mete, Mutlu Yip, Vincent Lee, Brendan Aydin, Kemal Univ Cent Arkansas Dept Comp Sci Conway AR 72035 USA Univ Arkansas Dept Comp Sci Pine Bluff AR 71601 USA

Motivation: the medical imaging and image processing techniques, ranging from microscopic to macroscopic, has become one of the main components of diagnostic procedures to assist dermatologists in their medical decision-making processes. Computer-aided segmentation and border detection on dermoscopic images is one of the core components of diagnostic procedures and therapeutic interventions for skin cancer. Automated assessment tools for dermoscopic images have become an important research field mainly because of inter- and intra-observer variations in human interpretations. In this study, a novel approach-graph spanner-for automatic border detection in dermoscopic images is proposed. In this approach, a proximity graph representation of dermoscopic images in order to detect regions and borders in skin lesion is presented. Results: Graph spanner approach is examined on a set of 100 dermoscopic images whose manually drawn borders by a dermatologist are used as the ground truth. Error rates, false positives and false negatives along with true positives and true negatives are quantified by digitally comparing results with manually determined borders from a dermatologist. the results show that the highest precision and recall rates obtained to determine lesion boundaries are 100%. However, accuracy of assessment averages out at 97.72% and borders errors' mean is 2.28% for whole dataset.

关键词： algorithms Humans image Interpretation, Computer-Assisted/methods Pattern Recognition, Automated/methods Skin Neoplasms/diagnosis Skin Neoplasms/pathology

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Quantifying the distribution of probes between subcellular locations using unsupervised pattern unmixing

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BIOINFORMATICS 2010年第12期26卷 i7-i12页

作者： Coelho, Luis Pedro Peng, Tao Murphy, Robert F. Carnegie Mellon Univ Lane Ctr Computat Biol Pittsburgh PA 15213 USA Carnegie Mellon Univ Ctr Bioimage informat Pittsburgh PA 15213 USA Carnegie Mellon Univ Joint Carnegie Mellon Univ Univ Pittsburgh Ph D Program Computat Biol Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Biomed Engn Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Biol Sci Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Machine Learning Pittsburgh PA 15213 USA Univ Freiburg Freiburg Inst Adv Studies D-79104 Freiburg Germany

Motivation: Proteins exhibit complex subcellular distributions, which may include localizing in more than one organelle and varying in location depending on the cell physiology. Estimating the amount of protein distributed in each subcellular location is essential for quantitative understanding and modeling of protein dynamics and how they affect cell behaviors. We have previously described automated methods using fluorescent microscope images to determine the fractions of protein fluorescence in various subcellular locations when the basic locations in which a protein can be present are known. As this set of basic locations may be unknown (especially for studies on a proteome-wide scale), we here describe unsupervised methods to identify the fundamental patterns from images of mixed patterns and estimate the fractional composition of them. Methods: We developed two approaches to the problem, both based on identifying types of objects present in images and representing patterns by frequencies of those object types. One is a basis pursuit method (which is based on a linear mixture model), and the other is based on latent Dirichlet allocation (LDA). For testing both approaches, we used images previously acquired for testing supervised unmixing methods. these images were of cells labeled with various combinations of two organelle-specific probes that had the same fluorescent properties to simulate mixed patterns of subcellular location. Results: We achieved 0.80 and 0.91 correlation between estimated and underlying fractions of the two probes (fundamental patterns) with basis pursuit and LDA approaches, respectively, indicating that our methods can unmix the complex subcellular distribution with reasonably high accuracy.

关键词： algorithms Fluorescent Dyes/analysis image processing, Computer-Assisted/methods Proteins/analysis Proteins/chemistry Subcellular Fractions/metabolism Subcellular Fractions/ultrastructure

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