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A New Technique for Solving a Jigsaw Puzzle

A New Technique for Solving a Jigsaw Puzzle

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IEEE International Conference on image Processing

作者： M. Makridis N. Papamarkos Image Processing and Multimedia Laboratory Department of Electrical & Computer Engineering Democritus University of Thrace Xanthi Greece

A new technique for solving jigsaw puzzles is proposed, which takes advantage of both geometrical and color features. It is considered that an image is being divided into a number of pieces (sub-images). The proposed technique is based on extraction of a set of boundary characteristic points and on a Kohonen self-organized feature map (KSOFM) color reduction technique. For each characteristic point a set of color and geometrical features are extracted. The technique compares these sets of features and decides whether two sub-images match or not. When a matching pair has been found, a corrective procedure is applied in order for these sub-images to fit exactly. Next, the proposed technique creates a new sub-image, which consists of the two matched sub-images. The whole matching procedure is being repeated until only one sub-image remains or no more matching sub-images can be found.

关键词： image analysis Shape image restoration image processing Laboratories Color Feature extraction image matching image reconstruction Proteins

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Fuzzy Edge Preserving Smoothing Filter Using Robust Region Growing

Fuzzy Edge Preserving Smoothing Filter Using Robust Region G...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： A. Mehrtash S. Vahdat H. Soltanian-Zadeh Electrical and Computer Engineering Department University of Tehran Tehran Iran School of Electrical Engineering Sharif University of Technology Tehran Iran Henry Ford Health System Radiology Image Analysis Laboratory Detroit USA USA Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Smoothing, while preserving edges, has always been a major challenge in image processing. In this paper, we propose a new approach that uses segmentation in order to avoid inter-region smoothing thus preserving the edges. It is common to smooth the image prior to region growing. The opposite procedure does not work properly in the presence of noise since region growing is very noise sensitive. To overcome this difficulty we adapted a robust region growing algorithm. Since region growing is very resource consuming, we do not perform it for every pixel. Instead, we divide the image into a number of overlapping blocks for which we carry out the segmentation. Then, we use the results for some of the core pixels in that block. Now that the regions are known, we proceed to smooth each region by a fuzzy approach emphasizing the pixels residing in it. The performance of this filter is compared to that of the bilateral filter and it is shown that the new method generates superior results.

关键词： Smoothing methods Filters Anisotropic magnetoresistance Filtering Pixel image segmentation Noise robustness Noise reduction image processing Partial differential equations

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Performance Modeling and Prediction of Face Recognition Systems

Performance Modeling and Prediction of Face Recognition Syst...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： Peng Wang Qiang Ji Section of Biomedical Image Analysis Department of Radiology University of Pennsylvania USA Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute USA

It is a challenging task to accurately model the performance of a face recognition system, and to predict its individual recognition results under various environments. This paper presents generic methods to model and predict the face recognition performance based on analysis of similarity measurement. We first introduce a concept of "perfect recognition", which only depends on the intrinsic structure of a recognition system. A metric extracted from perfect recognition similarity scores (PRSS) allows modeling the face recognition performance without empirical testing. This paper also presents an EM algorithm to predict the recognition rate of a query set. Furthermore, features are extracted from similarity scores to predict recognition results of individual queries. The presented methods can select algorithm parameters offline, predict recognition performance online, and adjust face alignment online for better recognition. Experimental results show that the performance of recognition systems can be greatly improved using presented methods.

关键词： Predictive models Face recognition Performance analysis image recognition Testing Feature extraction Biometrics Fingerprint recognition Prediction algorithms computer vision

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EKF-Based Recursive Dual Estimation of Structure & Motion from Stereo Data

EKF-Based Recursive Dual Estimation of Structure & Motion fr...

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International Symposium on 3D Data Processing Visualization and Transmission

作者： Hongsheng Zhang Shahriar Negahdaripour Underwater Vision and Imaging Laboratory Electrical and Computer Engineering Department University of Miami Coral Gables FL USA

Extended Kalman filters (EKF) have been proposed to estimate ego-motion and to recursively update scene structure in the form of 3-D positions of selected prominent features from motion and stereo sequences. Previous methods typically accommodate no more than a few dozen features for real-time processing. To maintain motion estimation accuracy, this calls for high contrast images to compute image feature locations with precision. Within manmade environments, various prominent corner points exist that can be extracted and tracked with required accuracy. However, prominent features are more difficult to localize precisely in natural scenes. Statistically, more feature points become necessary to maintain the same level of motion estimation accuracy and robustness. However, this imposes a computational burden beyond the capability of EKF-based techniques for real-time processing. A sequential dual EKF estimator utilizing stereo data is proposed for improved computation efficiency. Two important issues, unbiased estimation and stochastic stability are addressed. Furthermore, the dynamic feature set is handled in a more effective, efficient and robust way. Experimental results to demonstrate the merits of the new theoretical and algorithmic developments are presented.

关键词： Motion estimation Recursive estimation Layout Robustness State estimation Computational efficiency Noise measurement Parameter estimation Laboratories computer vision

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Multiresolution Object Recognition Using Dual Heuristic Programming

Multiresolution Object Recognition Using Dual Heuristic Prog...

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International Joint Conference on Neural Networks (IJCNN)

作者： F. Siddiqui K.M. Iftekharuddin Intelligent Systems and Image Processing Laboratory Department of Electrical and Computer Engineering University of Memphis Memphis TN USA

We present automatic target recognition (ATR) model based on principles of biological vision systems. The model employs reinforcement learning (RL) through Dual Heuristic Programming (DHP). The performance of the reported ATR model is compared to that of our previously reported ATR model, based on Heuristic Dynamic Programming (HDP). The HDP and DHP, known as the Adaptive Critic Designs (ACD), are neural network based implementation of Dynamic Programming (DP). The simulation shows promising results for both HDP and DHP based ATR model in presence of resolution distortion in incoming images and confirms that the DHP model is faster and more robust for our ATR system than the HDP.

关键词： Object recognition Learning Robustness Biological system modeling Machine vision Target recognition Dynamic programming Neural networks image resolution Nonlinear distortion

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BC&GC-Based Dense Stereo By Belief Propagation

BC&GC-Based Dense Stereo By Belief Propagation

引用

IEEE International Conference on computer vision Systems (ICVS)

作者： Hongsheng Zhang S. Negahdaripour Underwater Vision and Imaging Laboratory Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA

Belief propagation (BP) have emerged as powerful tools in the realm of dense stereo computation. However the underlying brightness constancy (BC) assumption of existing methods severely limit the range of their applications. Augmenting BC with gradient constancy (GC) assumption has lead to a more accurate algorithm for optical flow computation. In this paper, these constraints are utilized in the frameworks of BP to broaden the application of stereo vision for 3D reconstruction. Results from experiments with semi-synthetic and real data illustrate that an algorithm incorporating these models generally yields better estimates, where the BC assumption is violated.

关键词： Belief propagation Radiometry Robustness computer vision Brightness Optical computing image motion analysis Stereo vision Markov random fields Costs

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A New Technique for Hand Gesture Recognition

A New Technique for Hand Gesture Recognition

引用

IEEE International Conference on image Processing

作者： E. Stergiopoulou N. Papamarkos Department of Electrical & Computer Engineering Democritus University of Thrace Xanthi Greece Image Processing and Multimedia Laboratory Greece

A new method for hand gesture recognition is proposed which is based on an innovative self-growing and self-organized neural gas (SGONG) network. Initially, the region of the hand is detected by using a color segmentation technique that depends on a skin-color distribution map. Then, the SGONG network is applied on the segmented hand so as to approach its topology. Based on the output grid of neurons, palm geometric characteristics are obtained which in accordance with powerful finger features allow the identification of the raised fingers. Finally, the hand gesture recognition is accomplished through a probability-based classification method.

关键词： image segmentation Skin Fingers Chromium image recognition image analysis Neural networks Application software computer vision Hidden Markov models

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A Fully Pipelined Multiplierless Architecture for 2D Convolution with Quadrant Symmetric Kernels

A Fully Pipelined Multiplierless Architecture for 2D Convolu...

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IEEE Asia-Pacific Conference on Circuits and Systems

作者： Ming Z. Zhang Vijayan K. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

Design of a fully pipelined multiplierless digital architecture for computing 2D convolution utilizing the quadrant symmetry of the kernels is proposed in this paper. Pixels in the four quadrants of the kernel region with respect to an image pixel are considered simultaneously for computing the partial results of the convolution sum. The new architecture performs computations in log-domain by utilizing low complexity log2 and inverse-log2 approximation modules. An effective data handling strategy is developed in conjunction with the logarithmic modules to eliminate the necessity of the multipliers in the architecture. The proposed architecture is capable of performing convolution operations for 181.3 1024 times 1024 frames or 190.1 million outputs per second with 22 times 22 kernels in a Xilinx's Virtex XC2V2000-4ff896 FPGA at maximum clock frequency of 190.1 MHz. The throughput of the new design is 3.17 times higher when compared with that of the previous implementations (Zhang et al., 2005). Evaluation in Xilinx's core generator showed that the proposed design results in 60% reduction in hardware resource when compared to the design using pipelined multipliers

关键词： Convolution Kernel computer architecture Pixel Data handling Field programmable gate arrays Clocks Frequency Throughput Hardware

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Design of a Digital Architecture for Real-Time Video, Enhancement Based on Illuminance-Reflectance Model

Design of a Digital Architecture for Real-Time Video, Enhanc...

引用

Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Hau T. Ngo Ming Z. Zhang Li Tao Vijayan K. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

A design of a high performance digital architecture for a nonlinear image enhancement technique is presented in this paper. The image enhancement is based on illuminance-reflectance model which improves the visual quality of digital images and video captured under insufficient or non-uniform lighting conditions [1]. Systolic, pipelined and parallel design techniques are utilized effectively in the proposed FPGA-based architectural design to achieve real-time performance. Estimation and folding techniques are used in the hardware algorithmic design to achieve faster, simpler and more efficient architecture. The video enhancement system is implemented using Xilinx's multimedia development board that contains a VirtexII-X2000 FPGA and it is capable of processing approximately 66 Mega-pixels (Mpixels) per second.

关键词： Signal processing algorithms image enhancement Field programmable gate arrays Digital signal processing computer architecture image coding Streaming media Parallel processing Reflectivity Algorithm design and analysis

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Design of a High Performance Digital Architecture for Real-Time Correction of Radial Lens Distortion

Design of a High Performance Digital Architecture for Real-T...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Hau T. Ngo Vijayan K. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

The radial lens distortion correction technique based on least squares estimation corrects a distorted image by expanding it nonlinearly so that straight lines in the object space remain straight in the image space. An absolute pipelined architecture is designed to correct radial lens distortion in images by partitioning the distortion correction algorithm into four main modules. The architecture includes a COKDIC based rectangular to polar coordinate transformation module, a back mapping module for nonlinear transformation of corrected image space to distorted image space, a COKDIC based polar to rectangular coordinate transformation module, and a linear interpolation module to calculate the intensities of four pixels simultaneously in the corrected image space. The system parameters include the expanded/corrected image size, distorted image size, the back mapping coefficients, distortion center and the center of the corrected image. The hardware architecture can sustain a high throughput rate of 30 4-MegaPixel (Mpixels) frames per second (total of 120 Mpixels). The pipelined architecture design will facilitate the use of dedicated hardware that can be mounted along with the camera unit.

关键词： Optical design Lenses Nonlinear distortion Hardware Least squares approximation Algorithm design and analysis Partitioning algorithms Simultaneous localization and mapping Interpolation Pixel

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