A.E. Cetin

Flame detection in video using hidden Markov models

This paper proposes a novel method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color clues, flame flicker process is also detected by using a hidden Markov model. Markov models representing the flame and flame colored ordinary moving objects are used to distinguish flame flicker process from motion of flame colored moving objects. Spatial color variations in flame are also evaluated by the same Markov models, as well. These clues are combined to reach a final decision. False alarms due to ordinary motion of flame colored moving objects are greatly reduced when compared to the existing video based fire detection systems.

Adaptive polyphase subband decomposition structures for image compression

Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral regions of the original data. However, this approach leads to various artifacts in images having spatially varying characteristics, such as images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure which can be either linear or nonlinear vary according to the nature of the signal. This leads to improved image compression ratios. Simulation examples are presented.

A 2-D orientation-adaptive prediction filter in lifting structures for image coding

Lifting-style implementations of wavelets are widely used in image coders. A two-dimensional (2-D) edge adaptive lifting structure, which is similar to Daubechies 5/3 wavelet, is presented. The 2-D prediction filter predicts the value of the next polyphase component according to an edge orientation estimator of the image. Consequently, the prediction domain is allowed to rotate /spl plusmn/45/spl deg/ in regions with diagonal gradient. The gradient estimator is computationally inexpensive with additional costs of only six subtractions per lifting instruction, and no multiplications are required.

Signal recovery from wavelet transform maxima

The 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. >

Teager energy based feature parameters for speech recognition in car noise

In this letter, a new set of speech feature parameters based on multirate signal processing and the Teager energy operator is introduced. The speech signal is first divided into nonuniform subbands in mel-scale using a multirate filterbank, then the Teager energies of the subsignals are estimated. Finally, the feature vector is constructed by log-compression and inverse discrete cosine transform (DCT) computation. The new feature parameters have robust speech recognition performance in the presence of car engine noise.

Equiripple FIR filter design by the FFT algorithm

The fast Fourier transform (FFT) algorithm has been used in a variety of applications in signal and image processing. In this article, a simple procedure for designing finite-extent impulse response (FIR) discrete-time filters using the FFT algorithm is described. The zero-phase (or linear phase) FIR filter design problem is formulated to alternately satisfy the frequency domain constraints on the magnitude response bounds and time domain constraints on the impulse response support. The design scheme is iterative in which each iteration requires two FFT computations. The resultant filter is an equiripple approximation to the desired frequency response. The main advantage of the FFT-based design method is its implementational simplicity and versatility. Furthermore, the way the algorithm works is intuitive and any additional constraint can be incorporated in the iterations, as long as the convexity property of the overall operations is preserved. In one-dimensional cases, the most widely used equiripple FIR filter design algorithm is the Parks-McClellan algorithm (1972). This algorithm is based on linear programming, and it is computationally efficient. However, it cannot be generalized to higher dimensions. Extension of our design method to higher dimensions is straightforward. In this case two multidimensional FFT computations are needed in each iteration.

Real-time fire and flame detection in video

The paper proposes a novel method to detect fire and/or flame by processing the video data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color clues, flame and fire flicker are detected by analyzing the video in the wavelet domain. Periodic behavior in flame boundaries is detected by performing a temporal wavelet transform. Color variations in fire are detected by computing the spatial wavelet transform of moving fire-colored regions. Other clues used in the fire detection algorithm include irregularity of the boundary of the fire-colored region and the growth of such regions in time. All of the above clues are combined to reach a final decision.

Multichannel ECG data compression by multirate signal processing and transform domain coding techniques

A multilead electrocardiography (ECG) data compression method is presented. First, a linear transform is applied to the standard ECG lead signals, which are highly correlated with each other. In this way a set of uncorrelated transform domain signals is obtained. Then, the resulting transform domain signals are compressed using various coding methods, including multirate signal processing and transform domain coding techniques.<<ETX>>

Detection of microcalcifications in mammograms using higher order statistics

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.

A class of linear-phase regular biorthogonal wavelets

A class of biorthogonal systems leading to linear-phase wavelets is presented. A notable feature of this structure is that the wavelets are derived from a filter bank where the lowpass analysis filter is constrained to be a halfband filter. The authors derive finite impulse response (FIR) biorthogonal solutions from a pair of Lagrange halfband filters. They also consider infinite impulse response (IIR) biorthogonal solutions based on a pair of zero-phase halfband filters derived from Butterworth halfband filters.<<ETX>>