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International conference on Intelligent Computing and Control systems (ICICCS)

作者： Vaidya, Bhaumik Surti, Mustafa Vaghasiya, Parth Bordiya, Jay Jain, Jenish SCET Surat India

ISBN: (纸本)9781538627457

In this paper, image processing algorithms are designed using high level synthesis and implemented on different hardware platforms. These implementations are compared in terms of speed, latency and resource utilization on various hardware platforms. The use of pipelining to reduce the latency is illustrated with an example. Using high level synthesis the designer has the opportunity to employ libraries similar to OpenCV and can take advantage of the productivity benefits of working at a higher level of abstraction, while creating high-performance hardware. Basic image processing algorithms like calculating histogram, histogram equalization, averaging filter and laplacian filter are chosen to explain hardware acceleration using high level synthesis. The workflow of implementing high level C / C++ / SystemC code in hardware using vivado high level synthesis tool is explained along with implementation results of various image processing algorithms.

关键词： image processing vivado HLS Zynq SOC virtex 7 virtex 6 Spartan 6 Histogram Laplacian filter

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Autonomous text summarization using collective intelligence based on nature-inspired algorithm 4th

Autonomous text summarization using collective intelligence ...

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4th iCatse conference on Mobile and Wireless Technology, ICMWT 2017

作者： Tefrie, Kaleab Getaneh Sohn, Kyung-Ah Department of Computer Engineering Ajou University San5 Woncheon-dong Yeongtong-gu Suwon443-779 Korea Republic of

ISBN: (纸本)9789811052804

Thousands of years ago written language was introduced as a way of enhancing and facilitating communication. Fast forward to the twenty first century much has changed, especially the flow of data incrementing at fast rate and we should use the power of algorithms and hardware technology to understand text more clearly. With the Information age rising we are being cluttered with humongous data each day with no sign of it slowing. Humans have been trying to create ways on how to handle this continuous flow of text, image and video. And one of the categories of subjects regarding text is text summarization, given a document coming up with a reasonable summarized version of the original document. People have tried different aspects of summarizing to get a shorter yet an informative definition of document. This paper tries to utilize using nature inspired algorithms to implement an auto summarizer of text using pseudo-selected features. The main objective of this research is to use of cooperative nature-inspired algorithm specifically ant colony algorithm in text mining problems, in our case, text summarization. And throughout the paper we will try to show how this system can be achieved as well as show the performance and effectiveness of the measurement. We have used the standard data used to test summarization techniques, DUC data and at last comparing it to two algorithms for further analysis. © Springer Science+Business Media Singapore 2018.

关键词： Natural language processing systems

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Real-time full alignment and phasing of multiple-aperture imagers using focal-plane sensors on unresolved objects

Real-time full alignment and phasing of multiple-aperture im...

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conference on Space Telescopes and Instrumentation - Optical, Infrared, and Millimeter Wave

作者： vievard, S. Cassaing, F. Mugnier, L. M. Bonnefois, A. Montri, J. Univ Paris Saclay ONERA DOTA F-92322 Chatillon France Natl Astron Observ Japan Subaru Telescope 650 North Aohoku Pl Hilo HI 96720 USA Observ Paris LESIA 5 Pl Jules Janssen F-92195 Meudon France NINS AstroBiol Ctr 2-21-1 Osawa Mitaka Tokyo Japan

ISBN: (数字)9781510619500

ISBN: (纸本)9781510619500

The alignment of the sub-apertures is a major challenge for future segmented telescopes and telescope arrays. We show here that a focal plane wave-front sensor using only two images can fully and efficiently align a multiple aperture system, both for the alignment (large amplitude tip/tilt aberrations correction) and phasing (piston and small amplitude tip/tilt aberrations correction) modes. We derive a new algorithm for the alignment of the sub-apertures : ELASTICS. We quantify the novel algorithm performance by numerical simulations. We show that the residues are within the capture range of the fine algorithms. We also study the performance of LAPD, a recent real-time algorithm for the phasing of the sub-apertures. The closed-loop alignment of a 6 sub-aperture mirror provides experimental demonstration for both algorithms.

关键词： Telescopes Alignment Co-phasing Phased-array imaging systems Active or adaptive optics Wave-front sensing Multi-frame image processing

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Embedded Cell Count Algorithm for Cultured Tissue Characterization

Embedded Cell Count Algorithm for Cultured Tissue Characteri...

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18th International-Federation-of-Automatic-Control (IFAC) conference on Technology, Culture and International Stability (TECIS)

作者： Yusifli, Elmar Yahiaoui, Reda Lajoie, Isabelle Yusifov, Salahaddin UBFC Besancon Nanomed Lab Besancon France Femto ST Inst Besancon France Bourgogne Franche Comte Univ Besancon France Azerbaijan State Oil & Ind Univ Baku Azerbaijan

Regenerated tissue is a one of the wide developing research topics of nowadays. The characterization of tissue in culture permits to regulate its final mechanical properties and to test the influence of pharmaceutical and cosmetic products on it. For this purpose, an embedded vision system was developed in order to characterize the mechanical properties of tissue in culture. Thus, the aim of the present study was to develop an embedded, automated and portable cell count algorithm which can quantify the fibroblast cells from the fluorescent images taken by developed FPGA driven embedded high definition (HD) camera module. The developed algorithm was integrated into "uCell" software and tested on fluorescent images. The automated cell counting results were compared with manual counting and showed that the algorithm is reliable in 95% percentage of cases. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Biomedical systems Embedded vision systems image processing algorithms Control Application

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Automatical Syndesmophyte Contour Extraction from Lateral C Spine Radiographs 20th

Automatical Syndesmophyte Contour Extraction from Lateral C ...

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20th Polish conference on Biocybernetics and Biomedical Engineering (PCBBE)

作者： Nurzynska, Karolina Piorkowski, Adam Bielecka, Marzena Obuchowicz, Rafal Taton, Grzegorz Sulicka, Joanna Korkosz, Mariusz Silesian Tech Univ Fac Automat Control Elect & Comp Sci Inst Informat Ul Akad 16 PL-44100 Gliwice Poland AGH Univ Sci & Technol Dept Geoinformat & Appl Comp Sci A Mickiewicza 30 Av PL-30059 Krakow Poland Jagiellonian Univ Dept Radiol Coll Med Krakow Poland Jagiellonian Univ Dept Biophys Chair Physiol Fac MedMed Coll Krakow Poland Jagiellonian Univ Dept Rheumatol & Balneol Fac Med Med Coll Krakow Poland

ISBN: (纸本)9783319669052

This article describes the problem of segmentation of the spine for lateral C spine radiographs. In this case, the most frequently used approach is the Active Shape Model. The use of the Active Appearance Model is considered in this paper. Segmentation quality of sample data is tested for selected preprocessing and predetecting edge algorithms: Sobel filter, Canny edge detection algorithm, and Statistical Dominance Algorithm. The particularly important issue of precise description of contours is considered and partially tested. The aim is to deliver a good quality preliminary step to syntactic analysis of vertebrae using the generalized shape language.

关键词： image processing Radiograph Bone segmentation Active contour Active shape model Active appearance model

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Deep Learning for Hyperspectral image Classification on Embedded Platforms

Deep Learning for Hyperspectral Image Classification on Embe...

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International image processing, Applications and systems conference (IPAS)

作者： Siddharth Balakrishnan David Langerman Evan Gretok Alan D. George University of Pittsburgh Pittsburgh PA USA

Hyperspectral image (HSI) analysis refers to the processes used to identify and classify objects photographed using equipment that can image photons from a broad range of the electromagnetic spectrum. Downlinking such large images from space on radiation-resistant platforms with limited on-board computing power takes a large amount of time, memory, and other mission-critical resources. Performing such analysis in space before downlinking all images will save these resources by enabling a subset of images of interest to be downloaded rather than the entire set. The goal of this study is to benchmark and evaluate HSI-classification methods which incorporate deep learning on embedded platforms with limited computing resources. Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN) are the classification methods used in this study. These algorithms were executed on a desktop PC and two embedded platforms: the ODROID-C2 and the Raspberry Pi 3B. Accuracy, run-time, and memory benchmarks determined the optimal model for each platform. Based on results gathered in this research, CNN classification is recommended for the desktop PC due to its high accuracy of 97%. MLP classification is recommended for the embedded platforms under study, as it showcased the shortest run-time and second-highest accuracy.

关键词： Support vector machines Benchmark testing Hyperspectral imaging Feature extraction Predictive models Classification algorithms conferences

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visual Servo Strategy for Robot Soccer systems

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SENSORS AND MATERIALS 2018年第4期30卷 893-906页

作者： Shieh, Ming-Yuan Southern Taiwan Univ Sci & Technol Dept Elect Engn 1 Nan Tai St Tainan 71005 Taiwan

In this paper, we propose a visual servo strategy scheme for robot soccer systems. All the controls of androids are based on the image processing of top-view screens captured by an overhead CCD camera upon the game field. To separate the targets from the background, a self-organizing map neural network (SOMNN)-based image processing scheme is proposed, in which the gravity of every color is calculated using the algorithms of image filtering, division, and morphology. It provides the coordinates and heading angle of every soccer android using the information of color pitches. The decision-making subsystem adopts the A* algorithm to determine a collision-free, direct, and optimal path so that the androids can trace a ball faster and kick well. The experimental results in the real FIRA AndroSot games demonstrate the feasibility of the proposed visual control system.

关键词： visual path planning android soccer system self-organizing map neural network A* algorithm FIRA AndroSot game

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Implementation of Real-Time Connected Component Labeling Using FPGA

Implementation of Real-Time Connected Component Labeling Usi...

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IEEE International conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Tsung-Han Tsai Yuan-Chen Ho Chi-En Tsai Dept. of Electrical Engineering National Central University Taiwan

Connected Component Labeling (CCL) is one of the important process in the field of image processing. It can detect connected component in binary image and label them. This paper proposes a real-time single-scan CCL architecture and implementation in field-programmable gate array (FPGA) platform. This implementation has been completed on Xilinx Vertex-5 FPGA device and just used with the internal memory for storing component size and position rather than saving a whole image. It has been working at 60Hz for video of 640x480. The architecture runs in real-time while having reasonably low resource utilization, making integration with other real-time algorithms feasible.

关键词： Labeling Real-time systems Field programmable gate arrays Corporate acquisitions conferences Signal processing algorithms image processing

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Mapping and Automatic Post-processing of Indoor Environments by Extending visual SLAM

Mapping and Automatic Post-Processing of Indoor Environments...

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International conference on Audio, Language and image processing, ICALIP

作者： Alexander Albrecht Nina Heide Systems for Measurement Control and Diagnosis Fraunhofer Institute of Optronics System Technologies and Image Exploitation IOSB Karlsruhe Germany

Adequately represented indoor mapping is of great importance. For instance, the efficiency and safety of first responders gets significantly improved. Stereo SLAM algorithms achieve remarkable results, nevertheless some of their map representations have drawbacks. Point clouds can rarely be interpreted intuitively by human operators due to the absence of color and their sparsity. Nor do those point clouds represent a suitable input for possible post-processing. This paper contributes a supplementary enhancement tailored to visual SLAM algorithms. First, a method of creating dense colored point clouds is introduced, which is based on 3D reconstruction and visual SLAM algorithms. Second, a post-processing scheme is proposed, which condenses those point clouds to a blueprint-like map of the building by extracting wall segments. Evaluation is conducted on data recorded with a person-carried stereo camera setup in a typical indoor environment covering a track length of about 70 m. It is demonstrated that a dense colored point cloud has been successfully created and adds great value to intuitive interpretation by human operators. Furthermore, post-processing delivers promising results. A reliable extraction of wall segments is achieved for walls that are represented by a sufficient number of points.

关键词： Three-dimensional displays Cameras Simultaneous localization and mapping visualization Buildings Indoor environments Green buildings

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The algorithms for Segmentation of Text-Lines in Handwriting images

The Algorithms for Segmentation of Text-Lines in Handwriting...

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International conference on Smart City and systems Engineering (ICSCSE)

作者： Huo Liulei Kamil Moydin Abdusalam Dawut Askar Hamdulla Institute of Information Science and Engineering Xinjiang University Urumqi China

ISBN: (纸本)9781728113678;9781728113661

Text line segmentation from handwriting image is the basis of handwriting text image processing, and the accuracy of line segmentation plays a decisive role in handwriting identification, handwriting recognition, handwriting retrieval and other research fields. The accuracy of line segmentation may directly lead to the accuracy and efficiency of handwriting identification, character recognition and text retrieval. Because offline handwriting has lost the order of writing and other information, which makes it more difficult to segment the offline handwriting image. This paper mainly aims at the complexity of the segmentation problem caused by the diversity of off-line handwriting styles, such as tilt, adhesion, overlap and so on, and compares the related solutions in recent years. In the end, some problems in line segmentation research are put forward or omitted, which is more convenient for readers to understand the field.

关键词： image segmentation Adhesives Clustering algorithms Classification algorithms Curve fitting Handwriting recognition Writing

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