Browsing by Author "Ansari, R."

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Open Access
Automated detection and enhancement of microcalcifications in mammograms using nonlinear subband decomposition
(IEEE, 1997) Ansari, R.; Gürcan, M. Nafi; Yardımcı, Yasemin; Çetin, A. Enis
In this paper, computer-aided detection and enhancement of microcalcifications in mammogram images are considered. The mammogram image is first decomposed into subimages using a `subband' decomposition filter bank which uses nonlinear filters. A suitably identified subimage is divided into overlapping square regions in which skewness and kurtosis as measures of the asymmetry and impulsiveness of the distribution are estimated. All regions with high positive skewness and kurtosis are marked as a regions of interest. Next, an outlier labeling method is used to find the locations of microcalcifications in these regions. An enhanced mammogram image is also obtained by emphasizing the microcalcification locations. Linear and nonlinear subband decomposition structures are compared in terms of their effectiveness in finding microcalcificated regions and their computational complexity. Simulation studies based on real mammogram images are presented.
Open Access
Detection of microcalcifications in mammograms using higher order statistics
(Institute of Electrical and Electronics Engineers, 1997-08) Gürcan, M. N.; Yardımcı, Y.; Çetin, A. Enis; Ansari, R.
A new method for detecting microcalcifications in mammograms is described. In this method, the mammogram image is first processed by a subband decomposition filterbank. The bandpass subimage is divided into overlapping square regions in which skewness and kurtosis as measures of the asymmetry and impulsiveness of the distribution are estimated. The detection method utilizes these two parameters. A region with high positive skewness and kurtosis is marked as a region of interest. Simulation results show that this method is successful in detecting regions with microcalcifications.
Open Access
Detection of microcalcifications in mammograms using nonlinear subband decomposition and outlier labeling
(SPIE, 1997-02) Gürcan, M. Nafi; Yardımcı, Yasemin C.; Çetin, A. Enis; Ansari, R.
Computer-aided diagnosis will be an important feature of the next generation picture archiving and communication systems. In this paper, computer-aided detection of microcalcifications in mammograms using a nonlinear subband decomposition and outlier labeling is examined. The mammogram image is first decomposed into subimages using a nonlinear subband decomposition filter bank. A suitably identified subimage is divided into overlapping square regions in which skewness and kurtosis as measures of the asymmetry and impulsiveness of the distribution are estimated. A region with high positive skewness and kurtosis is marked as a region of interest. Finally, an outlier labeling method is used to find the locations of microcalcifications in these regions. Simulation studies are presented.
Open Access
Eye tracking using markov models
(IEEE, 2004) Bağcı, A. M.; Ansari, R.; Khokhar, A.; Çetin, A. Enis
We propose an eye detection and tracking method based on color and geometrical features of the human face using a monocular camera. In this method a decision is made on whether the eyes are closed or not and, using a Markov chain framework to model temporal evolution, the subject's gaze is determined. The method can successfully track facial features even while the head assumes various poses, so long as the nostrils are visible to the camera. We compare our method with recently proposed techniques and results show that it provides more accurate tracking and robustness to variations in view of the face. A procedure for detecting tracking errors is employed to recover the loss of feature points in case of occlusion or very fast head movement. The method may be used in monitoring a driver's alertness and detecting drowsiness, and also in applications requiring non-contact human computer interaction.
Open Access
Improved image-based localization using sfm and modified coordinate system transfer
(Institute of Electrical and Electronics Engineers, 2018) Salarian, M.; Iliev, N.; Çetin, A. Enis; Ansari, R.
Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database collected from social sharing websites like Flickr or services such as Google Street View. This paper proposes a new method for reliable estimation of the actual query camera location by optimally utilizing structure from motion (SFM) for three-dimensional (3-D) camera position reconstruction, and introducing a new approach for applying a linear transformation between two different 3-D Cartesian coordinate systems. Since the success of SFM hinges on effectively selecting among the multiple retrieved images, we propose an optimization framework to do this using the criterion of the highest intraclass similarity among images returned from retrieval pipeline to increase SFM convergence rate. The selected images along with the query are then used to reconstruct a 3-D scene and find the relative camera positions by employing SFM. In the last processing step, an effective camera coordinate transformation algorithm is introduced to estimate the query's geo-tag. The influence of the number of images involved in SFM on the ultimate position error is investigated by examining the use of three and four dataset images with different solution for calculating the query world coordinates. We have evaluated our proposed method on query images with known accurate ground truth. Experimental results are presented to demonstrate that our method outperforms other reported methods in terms of average error.
Open Access
A multiplication-free framework for signal processing and applications in biomedical image analysis
(IEEE, 2013) Suhre, A.; Keskin F.; Ersahin, T.; Cetin-Atalay, R.; Ansari, R.; Cetin, A.E.
A new framework for signal processing is introduced based on a novel vector product definition that permits a multiplier-free implementation. First a new product of two real numbers is defined as the sum of their absolute values, with the sign determined by product of the hard-limited numbers. This new product of real numbers is used to define a similar product of vectors in RN. The new vector product of two identical vectors reduces to a scaled version of the l1 norm of the vector. The main advantage of this framework is that it yields multiplication-free computationally efficient algorithms for performing some important tasks in signal processing. An application to the problem of cancer cell line image classification is presented that uses the notion of a co-difference matrix that is analogous to a covariance matrix except that the vector products are based on our new proposed framework. Results show the effectiveness of this approach when the proposed co-difference matrix is compared with a covariance matrix. © 2013 IEEE.
Open Access
Near-lossless image compression techniques
(S P I E - International Society for Optical Engineering, 1998) Ansari, R.; Memon, N.; Ceran, E.
Predictive and multiresolution techniques for near- lossless image compression based on the criterion of maximum allowable deviation of pixel values are investigated. A procedure for near-lossless compression using a modification of lossless predictive coding techniques to satisfy the specified tolerance is described. Simulation results with modified versions of two of the best lossless predictive coding techniques known, CALIC and JPEG-LS, are provided. Application of lossless coding based on reversible transforms in conjunction with prequantization is shown to be inferior to predictive techniques for near-lossless compression. A partial embedding two-layer scheme is proposed in which an embedded multiresolution coder generates a lossy base layer, and a simple but effective context-based lossless coder codes the difference between the original image and the lossy reconstruction. Results show that this lossy plus near-lossless technique yields compression ratios close to those obtained with predictive techniques, while providing the feature of a partially embedded bit-stream. © 1998 SPIE and IS&T.
Open Access
Real-time epileptic seizure detection during sleep using passive infrared sensors
(Institute of Electrical and Electronics Engineers Inc., 2019) Hanosh, O.; Ansari, R.; Younis, K.; Çetin, A. Enis
This paper addresses the problem of detecting epileptic seizures experienced by a human subject during sleep. Commonly used solutions to this problem mostly rely on detecting motion due to seizures using contact-based sensors or video-based sensors. We seek a low-cost, low-power alternative that can sense motion without making direct contact with the subject and provides high detection accuracy. We investigate the use of Passive InfraRed (PIR) sensors to sense human body motion caused by epileptic seizures during sleep which makes the body shake and causes the PIR sensor to generate an oscillatory output signal. This signal can be distinguished from that of ordinary motions during sleep using analysis with machine learning algorithms. The supervised hidden Markov model algorithm (HMM) and a 1-D and 2-D convolutional neural network (ConvNet) are used to classify the data set of the PIR sensor output into the occurrence of epileptic seizures, ordinary motions, or absence of motion. The method was tested on the PIR signals captured at 1 m from 33 recruited healthy subjects who, after watching seizure videos, either moved their body on a bed to simulate a seizure, ordinary motion, or lay still. The HMM algorithm attained 97.03% accuracy, while 1D-ConvNet and 2D-ConvNet attained an accuracy of 96.97% and 98.98%, respectively. All simulated seizures were successfully detected, with errors occurring only in distinguishing between ordinary motion and no motion, thereby demonstrating the potential for using PIR sensors in the epileptic seizure detection.
Open Access
Signal recovery from wavelet transform maxima
(IEEE, 1994-01) Çetin, A. Enis; Ansari, R.
This paper presents an iterative algorithm for signal recovery from discrete-time wavelet transform maxima. The signal recovery algorithm is developed by using the method of projections onto convex sets. Convergence of the algorithm is assured.
Open Access
Two-dimensional FIR filters
(CRC Press, 2003) Ansari, R.; Çetin, A. Enis; Chen, W. K.
In this chapter, methods of designing two-dimensional (2-D) finite-extent impulse response (FIR) discrete-time filters are described. Two-dimensional FIR filters offer the advantages of phase linearity and guaranteed stability, which makes them attractive in applications. Over the years an extensive array of techniques for designing 2-D FIR filters has been accumulated [14, 30, 23]. These techniques can be conveniently classified into the two categories of general and specialized designs. Techniques in the category of general design are intended for approximation of arbitrary desired frequency responses usually with no structural constraints on the filter. These techniques include approaches such as windowing of the ideal impulse response [22] or the use of suitable optimality criteria possibly implemented with iterative algorithms. On the other hand, techniques in the category of special design are applicable to restricted classes of filters, either due to the nature of the response being approximated or due to imposition of structural constraints on the filter used in the design. The specialized designs are a consequence of the observation that commonly used filters have characteristic underlying features that can be exploited to simplify the problem of design and implementation. The stopbands and passbands of filters encountered in practice are often defined by straight line, circular or elliptical boundaries. Specialized design methodologies have been developed for handling these cases and they are typically based on techniques such as the transformation of one-dimensional (1-D) filters or the rotation and translation of separable filter responses. If the desired response possesses symmetries, then the symmetries imply relationships among the filter coefficients which are exploited in both the design and the implementation of the filters. In some design problems it may be advantageous to impose structural constraints in the form of parallel and cascade connections.