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image registration for sequence of visual images captured by UAV

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

引用

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

作者： Matthew I. McCartney Saleh Zein-Sabatto Mohan Malkani College of Engineering Technology and Computer Science Tennessee State University USA

Unmanned aerial vehicles (UAVs) are regularly 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 ldquoweighed downrdquo 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.

关键词： image registration Unmanned aerial vehicles Satellite ground stations Surveillance Cameras Remote monitoring Collaborative software Payloads Reconnaissance Target tracking

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Using fuzzy rough feature selection for image retrieval system

Using fuzzy rough feature selection for image retrieval syst...

引用

ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Maryam Shahabi Lotfabadi Mohd Fairuz Shiratuddin Kok Wai Wong School of Information Technology Murdoch University Murdoch Australia

Feature selection is an important step in processing the images especially for applications such as content based image retrieval. In large multimedia databases, it may not be practical to search through the entire database in order to retrieve similar images from a query. Good data structures for similarity search and indexing are needed, and the existing data structures do not scale well for the high dimensional multimedia descriptors. Thus feature selection is an important step. Fuzzy rough feature selection method has many advantages in determining the relevant features. In this paper, five feature selection methods are compared with the fuzzy rough method. These five feature selection methods are Relief-F, Information Gain, Gain Ratio, OneR and the statistical measure χ 2 . The main purpose of the comparison is to rank the image features and see which method provides better results. An image retrieval dataset (COREL dataset) was used in the comparison. In order to evaluate the performance of the six methods, ranking of the important features is defined. This is then used to compare with the automated ranking produced by the aforesaid feature selection methods. Results show that the retrieval system using fuzzy rough feature selection has better retrieval accuracy and provide good Precision Recall performance. The advantages of the use of fuzzy rough feature selection will also be discussed in the paper.

关键词： image retrieval Accuracy Entropy Feature extraction Multimedia communication Gain measurement Vectors

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8 bit current-mode analog signal processing system for FAX scanners

8 bit current-mode analog signal processing system for FAX s...

引用

ieee International symposium on Circuits and Systems (ISCAS)

作者： M. Eyal R. Holzer National Semiconductor (I.C.) Limited Herzliya Israel

An analog module for processing a fax scanner's signals is presented. The module is a section of a complete solution fax system chip, which utilizes current mode CMOS circuits in a noisy environment to produce an 8-b resolution, 64 gray-level pictures from a low-cost (low performance) charge coupled device (CCD), or contact-type image sensor (CIS) scanners.< >

关键词： signal processing CMOS image sensors Circuit noise Working environment noise image resolution signal resolution Charge-coupled image sensors Charge coupled devices image sensors computational intelligence Society

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Cortical columns: Building blocks for intelligent systems

Cortical columns: Building blocks for intelligent systems

引用

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

作者： Atif G. Hashmi Mikko H. Lipasti Department of Electrical and Computer Engineering University of Wisconsin Madison USA

The neocortex appears to be a very efficient, uniformly structured, and hierarchical computational system. Researchers have made significant efforts to model intelligent systems that mimic these neocortical properties to perform a broad variety of pattern recognition and learning tasks. Unfortunately, many of these systems have drifted away from their cortical origins and incorporate or rely on attributes and algorithms that are not biologically plausible. In contrast, this paper describes a model for an intelligent system that is motivated by the properties of cortical columns, which can be viewed as the basic functional unit of the neocortex. Our model extends predictability minimization to mimic the behavior of cortical columns and incorporates neocortical properties such as hierarchy, structural uniformity, and plasticity, and enables adaptive, hierarchical independent feature detection. Initial results for an unsupervised learning task - identifying independent features in image data - are quite promising, both in a single-level and a hierarchical organization modeled after the visual cortex. The model is also able to forget learned patterns that no longer appear in the dataset, demonstrating its adaptivity, resilience, and stability under changing input conditions.

关键词： Intelligent systems Intelligent structures Biological system modeling computational intelligence Brain modeling Biology computing Pattern recognition Predictive models Computer vision Unsupervised learning

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Reconfigurable wireless stand-alone platform for Electrical Capacitance Tomography

Reconfigurable wireless stand-alone platform for Electrical ...

引用

ieee symposium on computational intelligence in Control and Automation, CICA

作者： W.A. Deabes M. Abdallah O. Elkeelany M.A. Abdelrahman Electrical Engineering Department Tennessee Technological University Cookeville TN USA

This paper presents the assessment of using field programmable gate arrays (FPGA) technology to design a stand-alone electrical capacitance tomography (ECT) system. ECT application is manifested by computationally intensive image reconstruction algorithms requiring fast processing of large amounts of data. To date, reconfigurable hardware has not been used in the area of electrical tomography. Furthermore, the experimental results show that using the FPGA as a hardware platform to realize ECT system achieves superior performance in terms of speed and design compactness compared to DSP implementation.

关键词： Electrical capacitance tomography Field programmable gate arrays Electrodes Hardware image reconstruction Capacitance measurement Casting Wireless sensor networks USA Councils Digital signal processing

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Real-time feature point tracking at 1000 fps

Real-time feature point tracking at 1000 fps

引用

ieee International symposium on computational intelligence in Robotics and Automation (CIRA)

作者： Idaku Ishii Ryo Sukenobe Yuta Moriue Kenkichi Yamamoto Hiroshima University Hiroshima Japan

ISBN: (纸本)9781424448081

Real-time feature point tracking at 1000 fps was performed by implementing a feature point tracking algorithm on a high-speed vision platform, which is improved for hardware integration and high-speed processing at real time. The high-speed vision platform on which the improved algorithm is hardware-implemented can be used to track feature points of 1024×1024 pixel images at 1000 fps. By considering fast-moving objects in the real world, we verified the performance of our developed real-time feature point tracking system.

关键词： Pixel Hardware Real time systems Tracking Field programmable gate arrays image processing Karhunen-Loeve transforms Feature extraction signal processing Robot vision systems

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Automated Blood Vessel Segmentation of Fundus images Using Region Features of Vessels

Automated Blood Vessel Segmentation of Fundus Images Using R...

引用

ieee symposium Series on computational intelligence

作者： Zhun Fan Jiewei Lu Yibiao Rong Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Department of Electronic Engineering Shantou University 515063 China Department of Electronic Engineering Shantou University Guangdong 515063 China

ISBN: (纸本)9781509042418

This paper proposes a novel and simple unsupervised vessel segmentation algorithm using fundus images. At first, the green channel of a fundus image is preprocessed to extract a binary image after the isotropic undecimated wavelet transform, and another binary image from the morphologically reconstructed image. Secondly, two initial vessel images are extracted according to the vessel region features for the connected regions in binary images. Next, the regions common to both initial vessel images are extracted as the major vessels. Then all remaining pixels in two initial vessel images are processed with skeleton extraction and simple linear iterative clustering. Finally the major vessels are combined with the processed vessel pixels. The proposed algorithm outperforms its competitors when compared with other widely used unsupervised and supervised methods, which achieves a vessel segmentation accuracy of 95.8% and 95.8% in an average time of 9.7s and 14.6s on images from two public datasets DRIVE and STARE, respectively.

关键词： Region Features Vessels

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An efficient method to reduce computational cost of improved super-resolution method

An efficient method to reduce computational cost of improved...

引用

ieee International symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Yasuo Takehisa Kiyoshi Tanaka Nagano General Industrial Technology Center Matsumoto Nagano Japan Faculty of Engineering Shinshu University Nagano Japan

In this paper, we propose a method to efficiently reduce computational cost of the improved super-resolution method that achieves dense motion estimation using overlapped block matching. We focus on statistics of motion vectors allocated to a small cell, and conjoin the calculation for same motion vectors in the optimization process. This method can reduce the entire computational cost up to 29.9 ~ 49.1% depending on a given video sequence in the case that maintains the original performance of the improved super-resolution method completely. If we relax the constraint that preserves the original performance, we can further reduce computational cost up to 20.7 ~ 27.8% without serious deterioration of the quality of reconstructed images.

关键词： computational efficiency signal resolution Motion estimation image reconstruction Video sequences image resolution Optimization methods Equations Noise generators computational intelligence

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Recurrent network-based face recognition using image sequences

Recurrent network-based face recognition using image sequenc...

引用

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

作者： Yong Ren Khan M. Iftekharuddin William E. White Department of Electrical and Computer Engineering University of Memphis Memphis TN USA

In this work, we propose a novel method for face recognition with large pose variations in image sequences using a cellular simultaneous recurrent network (CSRN).The pose problem is still a daunting challenge in face recognition. If the image sequences are obtained from different viewpoints in a surveillance type of application, the face recognition rate drops significantly. We formulate the recognition problem for face image sequences with large pose variation as an implicit temporal prediction task for CSRN. Further, to reduce the computational cost, we obtain eigenfaces for a set of image sequences for each person and use these reduced pattern vectors as the input to the CSRN. The CSRN is trained by this pattern vector, and each CSRN learns how to associate each face class/person in the training phase. When a new face is encountered, the corresponding image sequence is projected to each eigenface space to obtain the test pattern vectors. The Euclidian distances between successive frames of test and output pattern vectors indicate either a match or mismatch between the two corresponding face classes. We extensively evaluate our CSRN-based face recognition technique with 5 persons using publicly available VidTIMIT Audio-Video face dataset .In order to verify the performance of the CSRN, we also implement an Elman neural network for comparison. Our simulation shows that for this VidTIMIT Audio-Video face dataset with large pose variation, we can obtain an overall 65% (for rank 1) or 75% (for rank 2) face recognition accuracy better than the 55%(rank 1) recognition accuracy of Elman neural network.

关键词： Face recognition image sequences Recurrent neural networks Large-scale systems image recognition Cellular networks Testing Neural networks Robustness Eyes

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Instance-based location estimation algorithm for a pedestrian in multiple color dynamic images

Instance-based location estimation algorithm for a pedestria...

引用

ieee International symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Yutaka Hatakeyama Akimichi Mitsuta Kaoru Hirota Department of Computational Intelligence and Systems Science Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology Yokohama Japan Customer Solutions Development Company Limited Kawasaki Japan

Location estimation algorithm for a pedestrian is proposed for the real surveillance system based on color instances with color dynamic images under low illumination, where the proposed color instances consist of color-difference, moving possibility region, and previous detection objects in edge region using time series data. It provides useful detection result for too low illuminated situation. Experimental results for dynamic image taken under low illumination in streets show that detected frames with the proposed algorithm increase by 20% compared with detection result without color instances. The proposed algorithm is under consideration for use in a relatively poor security downtown area in Japan.

关键词： Color signal processing algorithms Surveillance Object detection image edge detection Cameras Lighting Detection algorithms computational intelligence Extraterrestrial measurements

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