Development of Multirate Filter – Based Region Features for Iris Identification

The emergence of biometric system is seen as the next-generation technological solution in strengthening the social and national security. The evolution of biometrics has shifted the paradigm of authentication from classical token and knowledge-based systems to physiological and behavioral trait based systems. R & D on iris biometrics, in last one decade, has established it as one of the most promising traits. Even though, iris biometric takes high resolution near-infrared (NIR) images as input, its authentication accuracy is very commendable. Its performance is often influenced by the presence of noise, database size, and feature representation. This thesis focuses on the use of multi resolution analysis (MRA) in developing suitable features for non-ideal iris images. Our investigation starts with the iris feature extraction technique using Cohen −Daubechies − Feauveau 9/7 (CDF 9/7) filter bank. In this work, a technique has been proposed to deal with issues like segmentation failure and occlusion. The experimental studies deal with the superiority of CDF 9/7 filter bank over the frequency based techniques. Since there is scope for improving the frequency selectivity of CDF 9/7 filter bank, a tunable filter bank is proposed to extract region based features from non-cooperative iris images. The proposed method is based on half band polynomial of 14th order. Since, regularity and frequency selectivity are in inverse relationship with each other, filter coefficients are derived by not imposing maximum number of zeros. Also, the half band polynomial is presented in x-domain, so as to apply semidefinite programming, which results in optimization of coefficients of analysis/synthesis filter. The next contribution in this thesis deals with the development of another powerful MRA known as triplet half band filter bank (THFB). The advantage of THFB is the flexibility in choosing the frequency response that allows one to overcome the magnitude constraints. The proposed filter bank has improved frequency selectivity along with other desired properties, which is then used for iris feature extraction. The last contribution of the thesis describes a wavelet cepstral feature derived from CDF 9/7 filter bank to characterize iris texture. Wavelet cepstrum feature helps in reducing the dimensionality of the detail coefficients; hence, a compact feature presentation is possible with improved accuracy against CDF 9/7. The efficacy of the features suggested are validated for iris recognition on three publicly available databases namely, CASIAv3, UBIRISv1, and IITD. The features are compared with other transform domain features like FFT, Gabor filter and a comprehensive evaluation is done for all suggested features as well. It has been observed that the suggested features show superior performance with respect to accuracy. Among all suggested features, THFB has shown best performance

Inspection of Parts with Complex Geometry and Welds with Structural Health Monitoring Techniques

Structural Health Monitoring (SHM) systems were developed to evaluate the integrity of a system during operation, and to quickly identify the maintenance problems. They will be used in future aerospace vehicles to improve safety, reduce cost and minimize the maintenance time of a system. Many SHM systems were already developed to evaluate the integrity of plates and used in marine structures. Their implementation in manufacturing processes is still expected. The application of SHM methods for complex geometries and welds are two important challenges in this area of research. This research work started by studying the characteristics of piezoelectric actuators, and a small energy harvester was designed. The output voltages at different frequencies of vibration were acquired to determine the nonlinear characteristics of the piezoelectric stripe actuators. The frequency response was evaluated experimentally. AA battery size energy harvesting devices were developed by using these actuators. When the round and square cross section devices were excited at 50 Hz frequency, they generated 16 V and 25 V respectively. The Surface Response to Excitation (SuRE) and Lamb wave methods were used to estimate the condition of parts with complex geometries. Cutting tools and welded plates were considered. Both approaches used piezoelectric elements that were attached to the surfaces of considered parts. The variation of the magnitude of the frequency response was evaluated when the SuRE method was used. The sum of the square of the differences was calculated. The envelope of the received signal was used for the analysis of wave propagation. Bi-orthogonal wavelet (Binlet) analysis was also used for the evaluation of the data obtained during Lamb wave technique. Both the Lamb wave and SuRE approaches along with the three methods for data analysis worked effectively to detect increasing tool wear. Similarly, they detected defects on the plate, on the weld, and on a separate plate without any sensor as long as it was welded to the test plate

Result-Biased Distributed-Arithmetic-Based Filter Architectures for Approximately Computing the DWT

The discrete wavelet transform is a fundamental block in several schemes for image compression. Its implementation relies on filters that usually require multiplications leading to a relevant hardware complexity. Distributed arithmetic is a general and effective technique to implement multiplierless filters and has been exploited in the past to implement the discrete wavelet transform as well. This work proposes a general method to implement a discrete wavelet transform architecture based on distributed arithmetic to produce approximate results. The novelty of the proposed method relies on the use of result-biasing techniques (inspired by the ones used in fixed-width multiplier architectures), which cause a very small loss of quality of the compressed image (average loss of 0.11 dB and 0.20 dB in terms of PSNR for the 9/7 and 10/18 wavelet filters, respectively). Compared with previously proposed distributed-arithmetic-based architectures for the computation of the discrete wavelet transform, this technique saves from about 20% to 25% of hardware complexity

Real-time spectral modelling of audio for creative sound transformation

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