Line spectral frequency representation of subbands for speech recognition

In this paper, a new set of speech feature parameters is constructed from subband analysis based Line Spectral Frequencies (LSFs). The speech signal is divided into several subbands and the resulting subsignals are represented by LSFs. The performance of the new speech feature parameters, SUBLSFs, is compared with the widely used Mel Scale Cepstral Coefficients (MELCEPs). SUBLSFs are observed to be more robust than the MELCEPs in the presence of car noise. © 1995

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 ±45° 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. © 2006 IEEE

Online detection of fire in video

This paper describes an online learning based method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. Our fire detection method consists of weak classifiers based on temporal and spatial modeling of flames. Markov models representing the flame and flame colored ordinary moving objects are used to distinguish temporal flame flicker process from motion of flame colored moving objects. Boundary of flames are represented in wavelet domain and high frequency nature of the boundaries of fire regions is also used as a clue to model the flame flicker spatially. Results from temporal and spatial weak classifiers based on flame flicker and irregularity of the flame region boundaries are updated online to reach a final decision. False alarms due to ordinary and periodic motion of flame colored moving objects are greatly reduced when compared to the existing video based fire detection systems. © 2007 IEEE

Volatile organic compound plume detection using wavelet analysis of video

A video based method to detect volatile organic compounds (VOC) leaking out of process equipments used in petrochemical refineries is developed. Leaking VOC plume from a damaged component causes edges present in image frames loose their sharpness. This leads to a decrease in the high frequency content of the image. The background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Plume regions in image frames are analyzed in low-band sub-images, as well. Image frames are compared with their corresponding low-band images. A maximum likelihood estimator (MLE) for adaptive threshold estimation is also developed in this paper. © 2008 IEEE

Lossless image compression using an edge adapted lifting predictor

We present a novel and computationally simple prediction stage in a Daubechies 5/3 - like lifting structure for lossless image compression. In the 5/3 wavelet, the prediction filter predicts the value of an odd-indexed polyphase component as the mean of its immediate neighbors belonging to the even-indexed polyphase components. The new edge adaptive predictor, however, predicts according to a local gradient direction estimator of the image. As a result, the prediction domain is allowed to flip + or - 45 degrees with respect to the horizontal or vertical axes in regions with diagonal gradient. We have obtained good compression results with conventional lossless wavelet coders. © 2005 IEEE

Restoration of error-diffused images using projection onto convex sets

In this paper, a novel inverse halftoning method is proposed to restore a continuous tone image from a given half-tone image. A set theoretic formulation is used where three sets are defined using the prior information about the problem. A new space-domain projection is introduced assuming the halftoning is performed using error diffusion, and the error diffusion filter kernel is known. The space-domain, frequency-domain, and space-scale domain projections are used alternately to obtain a feasible solution for the inverse halftoning problem which does not have a unique solution

Motion vector based features for content based video copy detection

In this article, we propose a motion vector based feature set for Content Based Copy Detection (CBCD) of video clips. Motion vectors of image frames are one of the signatures of a given video. However, they are not descriptive enough when consecutive image frames are used because most vectors are too small. To overcome this problem we calculate motion vectors in a lower frame rate than the actual frame rate of the video. As a result we obtain longer vectors which form a robust parameter set representing a given video. Experimental results are presented. © 2010 IEEE

Image feature extraction using 2D mel-cepstrum

In this paper, a feature extraction method based on two-dimensional (2D) mel-cepstrum is introduced. Feature matrices resulting from the 2D mel-cepstrum, Fourier LDA approach and original image matrices are individually applied to the Common Matrix Approach (CMA) based face recognition system. For each of these feature extraction methods, recognition rates are obtained in the AR face database, ORL database and Yale database. Experimental results indicate that recognition rates obtained by the 2D mel-cepstrum method is superior to the recognition rates obtained using Fourier LDA approach and raw image matrices. This indicates that 2D mel-cepstral analysis can be used in image feature extraction problems. © 2010 IEEE

Mel-cepstral methods for image feature extraction

A feature extraction method based on two-dimensional (2D) mel-cepstrum is introduced. The concept of one-dimensional (1D) mel-cepstrum which is widely used in speech recognition is extended to 2D in this article. Feature matrices resulting from the 2D mel-cepstrum, Fourier LDA, 2D PCA and original image matrices are converted to feature vectors and individually applied to a Support Vector Machine (SVM) classification engine for comparison. The AR face database, ORL database, Yale database and FRGC version 2 database are used in experimental studies, which indicate that recognition rates obtained by the 2D mel-cepstrum method is superior to the recognition rates obtained using Fourier LDA, 2D PCA and ordinary image matrix based face recognition. This indicates that 2D mel-cepstral analysis can be used in image feature extraction problems. © 2010 IEEE