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Canadian Conference on computer and Robot vision, CRV

作者： Mostafa Abdelrahman Moumen El-Melegy Aly Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Department Assiut University Asyut Egypt

One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse representation of scale-invariant heat kernel. We use the Laplace-Beltrami eigen functions to detect a small number of critical points on the shape surface. Then a shape descriptor is formed based on the heat kernels at the detected critical points for different scales, combined with the normalized eigen values of the Lap lace-Beltrami operator. Sparse representation is used to reduce the dimensionality of the calculated descriptor. The proposed descriptor is used for classification via the collaborative representation-based classification with regularized least square algorithm. We compare our approach to two well-known approaches on two different data sets: the nonrigid world data set and the SHREC 2011. The results have indeed confirmed the improved performance of the proposed approach, yet reducing the time and space complicity of the shape retrieval problem.

关键词： Shape Heating Eigenvalues and eigenfunctions Kernel Vectors Manifolds Heat transfer

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Multi-color ULBP with wavelet transform in invariant pose face recognition

Multi-color ULBP with wavelet transform in invariant pose fa...

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IEEE International Conference on Signal and image processing Applications (ICSIPA)

作者： Seyed Omid Shahdi S. A. R. Abu-Bakar Computer Vision Video and Image Processing (CvviP) Research Lab Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia

Variation in pose is one of the main obstacles confronting researchers in the area of face recognition. In this paper, a novel method is proposed to explicitly tackle this problem. Multi-color uniform local binary pattern (ULBP) is introduced for extracting salient features along with wavelet transform. Learning scheme is adopted to obtain a mapping coefficient vector between face in a pose and frontal face. Then expected frontal face view vector could be generated by inserting the posed face. Instead of using the entire face, some of its important regions are taken into account. The proposed method relies only on single frontal face image as a gallery image. Results have demonstrated that the proposed method operates well even under the low-resolution conditions.

关键词： Face Vectors Face recognition Feature extraction Wavelet transforms Conferences

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Frequency domain feature-based face recognition technique for different poses and low-resolution conditions

Frequency domain feature-based face recognition technique fo...

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Seyed Omid Shahdi S.A.R. Abu-Bakar Computer Vision Video and Image Processing (CvviP) Research Laboratory Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia

Pose variations are known to give real challenges in face recognition system. In this paper we proposed a method to recognize non-frontal faces with high performance by relying only on single full frontal gallery faces. By utilizing only small regions of the face or patches, we compute the Fourier coefficients of these patches for each image and transform them into a single vector. Hence, instead of comparing and matching pixels values we use these vectors to form a linear relationship which is then used to estimate the frontal face vector and then compare it with the actual frontal feature vector. The results show an average performance accuracy of 90% across all pose.

关键词： Face Face recognition Databases Feature extraction Training Vectors

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Thermographic image analysis method in detection of canine bone cancer (osteosarcoma)

Thermographic image analysis method in detection of canine b...

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Congress on image and Signal processing, CISP

作者： Maryamsadat Amini Peng Liu Scott E Umbaugh Dominic J. Marino Catherine A. Loughin Computer Vision and Image Processing Laboratory Electrical and Computer Engineering Southern Illinois University Edwardsville IL USA Long Island Veterinary Specialists Plainview NY USA

Bone cancer is a pathologic condition which may occur for both humans and canines. This tumor develops quickly from within the bone tissue and become painful as it grows outward. A metastasized bone tumor may be cured by amputation, otherwise it will be fatal. The current diagnostic imaging methods for bone cancer are X-rays, Computed Tomography scan (CT scan), and Magnetic Resonance Imaging (MRI). The disadvantages of these methods include not enough detail in X-ray images, high dose of radiation from CT scans, and high expense of the time-consuming MRI method. In most of the bone cancer cases, when this tumor is detected by these imaging methods, it has already metastasized. The study is to investigate whether it is possible to detect canine bone cancer by thermography imaging. This alternative imaging method will decrease diagnostic time, expenses and prevent radiation exposure. The best classification success rate obtained in this study is 80.77%.

关键词： Feature extraction image color analysis Cancer Pattern classification Bones Software Histograms

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A comparision of Model-based methods for knee cartilage segmentation

A comparision of Model-based methods for knee cartilage segm...

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2nd International Conference on computer vision Theory and Applications, VISAPP 2007

作者： Cheong, J. Faggian, N. Langs, G. Suter, D. Cicuttini, F. Dept. of Electrical Dept. of Computer Systems Engineering Monash University Australia Clayton School of Information Technology Monash University Australia Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria Dept. of Epidemiology Dept. of Preventive Medicine Monash University Australia

Osteoarthritis is a chronic and crippling disease affecting an increasing number of people each year. With no known cure, it is expected to reach epidemic proportions in the near future. Accurate segmentation of knee cartilage from magnetic resonance imaging (MRI) scans facilitates the measurement of cartilage volume present in a patient's knee, thus enabling medical clinicians to detect the onset of osteoarthritis and also crucially, to study its effects. This paper compares four model-based segmentation methods popular for medical data segmentation, namely Active Shape Models (ASM) (Cootes et al., 1995), Active Appearance Models (AAM) (Cootes et al., 2001), Patch-based Active Appearance Models (PAAM) (Faggian et al., 2006), and Active Feature Models (AFM) (Langs et al., 2006). A comprehensive analysis of how accurately these methods segment human tibial cartilage is presented. The results obtained were benchmarked against the current "gold standard" (cartilage segmented manually by trained clinicians) and indicate that modeling local texture features around each landmark provides the best results for segmenting human tibial cartilage.

关键词： Medical imaging

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Enhancement of stents using interference of low-frequency ultrasonic echo signals

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Journal of Medical Ultrasonics 2004年第2期31卷 67-73页

作者： Ohashi, Gosuke Ohya, Akihisa Tobise, Kazimobu Akiyama, Iwaki Faculty of Engineering Shizuoka University Hamamatsu Japan Institute of Information Sciences and Electronics University of Tsukuba Tsukuba Japan Shoryo Electronic Corporation Kamakura Japan Faculty of Engineering Shonan Institute of Technology Fujisawa Japan Image Processing and Vision Research Laboratory Department of Electrical and Computer Engineering University of California at Santa Barbara Santa Barbara CA 93106-9560 United States

Purpose. We set out to enhance the imaging of stents used for coronary coarctation surgery without imaging the reticulation of the stent. Because the stent is a reticulated structure, there is a relation between ultrasound wavelength and the interstice reticulation that produces the echo. Methods. First we performed computer simulation by ultrasound frequency of transmitted signals to analyze this relation. Then, instead of controlling the transmitted wave, we processed the returned signals through a band-pass filter because of the difficulty of controlling the transmitted waves of diagnostic ultrasound equipment. Following this, we conducted experiments on an agar gel phantom containing a stent to verify the effectiveness of this method. Results. The simulation confirmed that the stent was apparent when the ultrasonic wavelength equaled the product of an integer and twice the interval of the reticulation of the stent. Application of a band-pass filter of 0.8 to 1.5MHz to the waveform returned from the agar gel phantom containing the stent. Conclusions. The effectiveness of this method in depicting the stent was confirmed. © The Japan Society of Ultrasonics in Medicine 2004.

关键词： Interference Received waveform Signal processing Stent Ultrasonic echography

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Morphological based target enhancement algorithms

Morphological based target enhancement algorithms

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Multidimensional Signal processing Workshop

作者： C.H.G. Wright E.J. Delp N.C. Gallagher USAF Space Division CA USA Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

Summary form only given, as follows. A necessary requirement of a strategic defense system is the detection of incoming nuclear warheads in an environment that may include nuclear detonations of undetected or missed target warheads. A computer model that simulates incoming warheads as distant endoatmospheric targets is described. A model of the expected electromagnetic noise present in a nuclear war environment is developed using estimates of the probability distributions. Predicted atmospheric effects are also included. Nonlinear morphological image enhancement algorithms are presented, and their ability to suppress the noise and atmospheric effects of the nuclear environment is discussed. Particular attention is given to the design of structure elements to mitigate the noise effects. These algorithms are then tested, using the combined target and noise models, and evaluated in terms of noise removal and the ability to resolve closely spaced targets.

关键词： Working environment noise Atmospheric modeling Nuclear weapons Military computing Computational modeling computer simulation Electromagnetic modeling Electromagnetic interference Probability distribution image enhancement

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Automatic mask creation and feature analysis for detectionof IVDD in canines

Automatic mask creation and feature analysis for detectionof...

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International Conference on computer Sciences and Convergence Information Technology (ICCIT)

作者： Jakia Afruz Jesse Phelps Scott E Umbaugh Dominic J. Marino Catherine A. Loughin Computer Vision and Image Processing Laboratory Electrical and Computer Engineering Southern Illionis University Edwardsville Edwardsville IL USA Long Island Veterinary Specialists Plainview NY USA

Intervertebral disc disease (IVDD) is a condition that affects both humans and canines. This disease is painful and degrades the quality of life for those that suffer from it. The current diagnostic methods for this disease are Magnetic Resonance Imaging (MRI) and/or Computed Axial Tomography (CAT scan). Both of these diagnostic methods are expensive and time consuming and involve patients being exposed to radiation and strong magnetic fields. In canines in particular, the amount of time it takes to perform one of these scans makes it necessary to sedate the animal as the patient needs to be still during the diagnostic procedure. Use of thermographic imaging for diagnosis, or at least prescreening, patients for IVDD will save money, time and possibly prevent needless radiation exposure. This paper attempts to show that thermal imaging of patients that are candidates for IVDD may be used diagnostically or as a prescreening method.

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Evaluation of geometric feature descriptors for detection and classification of lung nodules in low dose CT scans of the chest

Evaluation of geometric feature descriptors for detection an...

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IEEE International Symposium on Biomedical Imaging

作者： Amal Farag Asem Ali James Graham Aly Farag Salwa Elshazly Robert Falk Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA Medical Imaging Division Jewish Hospital Louisville KY USA

This paper examines the effectiveness of geometric feature descriptors, common in computer vision, for false positive reduction and for classification of lung nodules in low dose CT (LDCT) scans. A data-driven lung nodule modeling approach creates templates for common nodule types, using active appearance models (AAM); which are then used to detect candidate nodules based on optimum similarity measured by the normalized cross-correlation (NCC). Geometric feature descriptors (e.g., SIFT, LBP and SURF) are applied to the output of the detection step, in order to extract features from the nodule candidates, for further enhancement of output and possible reduction of false positives. Results on the clinical ELCAP database showed that the descriptors provide 2% enhancements in the specificity of the detected nodule above the NCC results when used in a k-NN classifier. Thus quantitative measures of enhancements of the performance of CAD models based on LDCT are now possible and are entirely model-based. Most importantly, our approach is applicable for classification of nodules into categories and pathologies.

关键词： Feature extraction Lungs Training Databases Solid modeling Principal component analysis Computed tomography

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Improving the Robustness of a Direct Visual Odometry Algorithm for Planetary Rovers

Improving the Robustness of a Direct Visual Odometry Algorit...

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International Conference on electrical engineering, Computing Science and Automatic Control (CCE)

作者： Geovanni Martinez Image Processing and Computer Vision Research Laboratory (IPCV-LAB) School of Electrical Engineering University of Costa Rica San José Costa Rica

An algorithm capable of computing the robot position by evaluating measurements of frame to frame intensity differences was extended to be able to detect outliers in the measurements to exclude them from the evaluation to perform the positioning, with the aim of improving its robustness in irregular terrain scenes, such as consisting of flat surfaces with stones on them. The images are taken by a camera firmly attached to the robot, tilted downwards, looking at the planetary surface. A measurement is detected as an outlier only if its intensity difference and linear intensity gradients can not be described by motion compensation. According to the experimental results, this modification reduced the positioning error by a factor of one third in difficult terrain, maintaining its positioning error, which resulted in an average of 1.8%, within a range of 0.15% and 2.5% of distance traveled, similar to those achieved by state of the art algorithms successfully used in robots here on earth and on Mars.

关键词： Three-dimensional displays Cameras Visual odometry Robot vision systems Wheels Extraterrestrial measurements

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