Abstract:

Nondestructive evaluation (NDE) is a noninvasive technique to determine the integrity of a material, component or structure or quantitatively measure some characteristic of an object. Industrial firms such as Siemens have seen the need to offer their customers more advanced NDE solutions. This dissertation discusses the image processing algorithms and their applications in NDE for both medical and transportation areas.

Medical ultrasound image registration is an essential component in an increasing number of applications, and has therefore been the subject of many studies in the literature. These applications use either generic registration algorithms or pixel-to-pixel comparison based ultrasound-specific methods. Hence, they are not well suited for the case of speckled images resulting from different realizations of a random process. To better handle the speckle, this dissertation proposes an information-theoretic feature detector-based registration approach. Using speckle modeling based on the distributions of Rayleigh or normalized Fisher-Tippett, a speckle-specific information-theoretic feature detector is constructed and applied to provide feature images. Those feature images are then registered using differential equations. Compared to standard gradient-based techniques, the experimental results demonstrate the effectiveness of the proposed method, particularly for low contrast ultrasound images.

Assessment of blood flow velocity in Doppler images is of great importance in clinical studies and research as well. This dissertation proposes an automated technique based on image processing and computer vision algorithms for real-time tracing of the waveform envelope in a sequence of pulsed Doppler images. Both the theory and implementation of the methodology are presented, and the experimental results demonstrate its ability to accurately trace the blood flow velocity in pulse wave Doppler images and its robustness to noise and computational efficiency.

Accurate assessment of the conditions of bridges leads to efficient economic rehabilitation management. This part of work discusses two effective technologies: Impact Echo (IE) and Ground Penetrating Radar (GPR). They are of special benefit in evaluation of corrosion-induced deck delamination, due to their nondestructive nature, speed of evaluation and ability to detect delaminated zones. A three dimensional (3D) IE data visualization and interpretation framework for the assessment of concrete bridge decks is presented in this dissertation. The proposed visualization and related interpretation techniques can be used to both enhance and simplify the interpretation of results of testing on delaminated bridge decks. Also, this dissertation for the first time proposes a novel method based on partial differential equations (PDEs) to discriminate rebar mat signatures for automated bridge deck delamination detection in GPR scans. A framework of computer-aided automated diagnosis for bridge health is presented in this dissertation.

Committee Members:

Dr. Mengchu Zhou (Co-Advisor), Professor, ECE Dept., NJIT
Dr. Tong Fang (Co-Advisor), Manager, Siemens Corporate Research
Dr. Nirwan Ansari, Professor, ECE Dept., NJIT
Dr. Yun-Qing Shi, Professor, ECE Dept., NJIT
Dr. John D. Carpinelli, Professor, ECE Dept., NJIT

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Note: All MS thesis and PhD dissertation (proposal) defense are counted towards ECE791.