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ieee symposium on computational intelligence in Vehicles and Transportation Systems (CIVTS)

作者： Zorig, Anar Haginiwa, Atsushi Sato, Hiroyuki Iwate Prefectural Univ Grad Sch Software & Informat Sci Takizawa Iwate 0200693 Japan

ISBN: (纸本)9781479944972

In our research, we have studied the autonomous running control system of the automatic guided vehicles (AGV) used in the manufacturing facilities using the tablet PC. The moving direction of automatic vehicle is controlled by the results of image processing methods on captured images of the tablet PC. In the image processing step, after detecting edges we obtain wall-floor boundaries by analyzing those edges. By applying the least square method on the wall-floor boundaries, we calculate the moving direction of the AGV. To improve the accuracy of the moving direction, we divide the edge detection image into grid cells and remove all edges in cells with sparse edges. Furthermore, we divided all boundary points into vertical subdivisions, estimated unusual small boundaries and discarded them. As a result of our research, the running distance of the AGV was improved from 10 meters to the whole length of the testing course. The distance of testing course is 100 meters long.

关键词： Tablet PC Android Autonomous running image processing

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Performance evaluation of image smoothing on CPU and GPU using multithreading - An experimental apwwWroach in High Performance Computing

Performance evaluation of image smoothing on CPU and GPU usi...

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7th ieee International Conference on computational intelligence and Computing Research (ICCIC)

作者： Gopalakrishnan, Anantharaman Narayanasamy, Senthil Anand Sethumadhavan, Gopalakrishnan Zoho Corp Chennai Tamil Nadu India SASTRA Univ Dept Comp Applicat Thanjavur India

ISBN: (纸本)9781509006120

The processing techniques and time consumed during the execution of a task in CPU and GPU vary depending on the technology of the architecture and their configuration. This paper compares the time consumed and the efficiency of CPU and GPU with different architectures and configurations to apply spatial smoothing filters on the images of a fixed spatial resolution. The processing speed was increased by 20 to 40 times, when GPU was used rather than CPU. Moreover, the processing time decreased further when filter specific configurations were used.

关键词： image smoothing multithread filters CPU GPU High Performance Computing

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Adaptive enhancement of historical document images

Adaptive enhancement of historical document images

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7th ieee International symposium on signal processing and Information Technology

作者： Kishore, N. Krishna Rege, Priti P. Coll Engn Dept Elect & Telecommun Pune Maharashtra India

ISBN: (纸本)9781424418343

In this paper we present a simple and computationally efficient method for document image enhancement. We use Unsharp masking to enhance the edge detail information in the degraded document. This image is then used to adjust the local threshold for each pixel. Proposed method is experimentally compared with Laplacian sign method and the Otsu method. It is shown that the method improves sharpness of the image with nearly half computational time.

关键词： image enhancement

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The Gestalt Interest Points Distance Feature for Compact and Accurate image Description 17

The Gestalt Interest Points Distance Feature for Compact and...

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17th ieee International symposium on signal processing and Information Technology (ISSPIT)

作者： Hoerhan, Markus Eidenberger, Horst Vienna Univ Technol Inst Software Technol & Interact Syst Favoritenstr 9-1882 A-1040 Vienna Austria

ISBN: (纸本)9781538646625

In this work, we present the novel Inter-GIP Distances (IGD) feature and its integration into the Gestalt Interest Points (GIP) image descriptor. With the ongoing growth of visual data, efficient image descriptor methods are becoming more and more important. Several local point-based description methods have been defined in the past decades. Accuracy and descriptor size are important factors when selecting the appropriate method for a given retrieval problem. The method presented in this work describes images with only a few very compact descriptors. To test our descriptor, we developed an image classification prototype and conducted several experiments with a publicly available horses dataset and a food dataset. Our experiments show that only a few of the very compact GIP image descriptors are necessary to quickly classify the images from the datasets with high accuracy. Furthermore, we compared our experimental results to state-of-the-art local point-based description methods and found that our method is highly competitive.

关键词： Feature extraction signal processing algorithms Visualization Robustness computational complexity signal processing Information technology

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Low-Cost Fourier Ptychography Microscope Kit 22

Low-Cost Fourier Ptychography Microscope Kit

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22nd symposium on image, signal processing and Artificial Vision (STSIVA)

作者： Guzman, Felipe Vera, Esteban Pontificia Univ Catolica Valparaiso Escuela Ingn Elect Valparaiso Chile

ISBN: (纸本)9781728114910

We present an advanced low-cost wide-field, high-resolution computational microscope kit based on Fourier ptychography. The microscope is integrated by using a collection of easy to find off-the-shelf components. By implementing the Fourier Ptychographic Microscopy (FPM) technique, we are able to acquire and synthetically produce wide field-of-view images at high resolutions, exceeding the original limitations of the optical system. The system works by iteratively updating a mosaiced high resolution Fourier spectrum from a collection of images of a sample captured at different illumination angles. We provide with the design of the low-cost kit and also with the results obtained by several tests performed with a calibration target and blood samples. From the results, the increase in resolution of the system is quantitatively and qualitatively demonstrated, while preserving the original wide field-of-view of the objective lens used.

关键词： Fourier ptychography microscopy phase retrieval computational imaging

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Simple Computer Vision System for Chess Playing Robot Manipulator as a Project-based Learning Example

Simple Computer Vision System for Chess Playing Robot Manipu...

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ieee International symposium on signal processing and Information Technology

作者： Sokic, Emir Ahic-Djokic, Melita Univ Sarajevo Fac Elect Engn Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9781424435548

This paper presents an example of project-based learning (PBL) in an undergraduate course on image processing. The design of a simple, low-cost computer vision system for implementation on a chess-playing capable robot is discussed. The system is based on a standard CCD camera and a personal computer. This project is a good tool for learning most of the course material that would otherwise be mastered by homework problems and study before an exam. An algorithm which detects chess moves is proposed. It compares two or more frames captured before, during and after a played chess move, and finds differences between them, which are used to define a played chess move. Further image processing is required to eliminate false readings, recognize direction of chess moves, end eliminate image distortion. Many image processing problems and solutions can be introduced to students, through the proposed algorithm. The results are encouraging - students without any previous knowledge in image processing and advanced topics, such as artificial intelligence (neural networks etc.), may attain a chess move recognition success rate greater than 95%, in controlled light environments. Keywords-image processing, project-based learning, robot manipulator, chess moves recognition success rate greater than 95%, in controlled light environments.

关键词： image processing project-based learning robot manipulator chess moves recognition

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Robotic Manipulation of Pathological Slides Powered by Deep Learning and Classical image processing 22

Robotic Manipulation of Pathological Slides Powered by Deep ...

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ieee Joint 22nd International symposium on computational intelligence and Informatics / 8th ieee International Conference on Recent Achievements in Mechatronics, Automation, Computer Science and Robotics (CINTI-MACRo)

作者： Karoly, Artur I. Tirczka, Sebestyen Piricz, Tamas Galambos, Peter Obuda Univ Antal Bejczy Ctr Intelligent Robot Becsi U 96-B H-1034 Budapest Hungary

ISBN: (纸本)9798350398823

Digital pathology has many advantages, so the need for digitizing already existing archives naturally arises. However, the fact that there is no standard way of storing pathology archives makes it difficult to provide an automated solution. In this paper, we tackle this problem with a robotic system, which uses a deep convolutional neural network and traditional image processing methods to automatically detect and localize the pathology samples and perform pick and place to organize the samples in a rack that can be directly inserted into the whole slide imaging (WSI) scanner. We were able to achieve a 90% success rate for the pick and place process. This paper introduces the hardware setup and software components that we used for our system and briefly explains the detection procedure.

关键词： Pathology

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Fuzzy Random Impulse Noise Removal From Color image Sequences

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ieee TRANSACTIONS ON image processing 2011年第4期20卷 959-970页

作者： Melange, Tom Nachtegael, Mike Kerre, Etienne E. Univ Ghent Dept Appl Math & Comp Sci Fuzziness & Uncertainty Modeling Res Unit B-9000 Ghent Belgium

In this paper, a new fuzzy filter for the removal of random impulse noise in color video is presented. By working with different successive filtering steps, a very good tradeoff between detail preservation and noise removal is obtained. One strong filtering step that should remove all noise at once would inevitably also remove a considerable amount of detail. Therefore, the noise is filtered step by step. In each step, noisy pixels are detected by the help of fuzzy rules, which are very useful for the processing of human knowledge where linguistic variables are used. Pixels that are detected as noisy are filtered, the others remain unchanged. Filtering of detected pixels is done by blockmatching based on a noise adaptive mean absolute difference. The experiments show that the proposed method outperforms other state-of-the-art filters both visually and in terms of objective quality measures such as the mean absolute error (MAE), the peak-signal-to-noise ratio (PSNR) and the normalized color difference (NCD).

关键词： Circuits and systems computers and information processing computational and artificial intelligence filtering filters fuzzy logic image denoising logic nonlinear filters

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image registration for sequence of visual images captured by UAV

Image registration for sequence of visual images captured by...

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2009 ieee symposium computational intelligence for Multimedia signal and Vision processing, CIMSVP 2009

作者： McCartney, Matthew I. Sabato, Saleh Zein Malkani, Mohan College of Engineering Technology and Computer Science Tennessee State University United States

ISBN: (纸本)9781424427710

Unmanned Aerial Vehicles (UAVs) areregularly outfitted with payloads that include high resolution surveillance cameras. These surveillance systems have provided the military with the opportunity to monitor battlefields and remote terrain, carryout reconnaissance missions and track targets all from distant ground stations without endangering UAV operators. As with any remote sensing technology there are technical challenges that exist. The problem often arises where large sequences of images containing significant redundancies are being sent to the ground station processing systems and operators. Consequently, the ground station systems can become "weighed down" and operators can become overwhelmed. In addition, the decision making process of detection and recognition algorithms could be rendered ineffective because of the limited visual field of view of individual image frames. In this research image registration software is designed and implemented to integrate a sequence of visual images based on the modified Scale-Invariant Feature Transform(SIFT) algorithm. Since computational efficiency is a critical issue in any real-time interactive system, a modified version of the SIFT algorithm is devised and utilized in this work. Implementation and testing results of the developed software are obtained from real data collected from aerial footage and a collaborative camera network. © 2009 ieee.

关键词： image registration

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Video Summarization based on Subclass Support Vector Data Description

Video Summarization based on Subclass Support Vector Data De...

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ieee symposium Series on computational intelligence

作者： Mygdalis, Vasileios Iosifidis, Alexandros Tefas, Anastasios Pitas, Ioannis Aristotle Univ Thessaloniki Dept Informat Thessaloniki Greece

ISBN: (纸本)9781479945092

In this paper, we describe a method for video summarization that operates on a video segment level. We formulate this problem as the one of automatic video segment selection based on a learning process that employs salient video segment paradigms. We design an hierarchical learning scheme that consists of two steps. At the first step, an unsupervised process is performed in order to determine salient video segment types. The second step is a supervised learning process that is performed for each of the salient video segment type independently. For the latter case, since only salient training examples are available, the problem is stated as an one-class classification problem. In order to take into account subclass information that may appear in the video segment types, we introduce a novel formulation of the Support Vector Data Description method that exploits subclass information in its optimization process. We evaluate the proposed approach in three Hollywood movies, where the performance of the proposed Subclass SVDD (SSVDD) algorithm is compared with that of related methods. Experimental results show that the adoption of both hierarchical learning and the proposed SSVDD method contribute to the final classification performance.

关键词： image classification image segmentation support vector machines unsupervised learning video signal processing Hollywood movies SSVDD algorithm automatic video segment selection hierarchical learning scheme one-class classification problem optimization process salient video segment types subclass support vector data description unsupervised process video summarization Feature extraction Motion pictures Optimization Streaming media Support vector machines Training Vectors Support Vector Network Cinema Streaming Video Optimization Procedure Video signal processing Unsupervised learning Videotapes image classification support vector data description Feature extraction Films image segmentation Segment Type Functional training Learning processes

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