Hierarchical Object Recognition Using Libraries of Parameterized Model Sub-Parts

This thesis describes the development of a model-based vision system that exploits hierarchies of both object structure and object scale. The focus of the research is to use these hierarchies to achieve robust recognition based on effective organization and indexing schemes for model libraries. The goal of the system is to recognize parameterized instances of non-rigid model objects contained in a large knowledge base despite the presence of noise and occlusion. Robustness is achieved by developing a system that can recognize viewed objects that are scaled or mirror-image instances of the known models or that contain components sub-parts with different relative scaling, rotation, or translation than in models. The approach taken in this thesis is to develop an object shape representation that incorporates a component sub-part hierarchy- to allow for efficient and correct indexing into an automatically generated model library as well as for relative parameterization among sub-parts, and a scale hierarchy- to allow for a general to specific recognition procedure. After analysis of the issues and inherent tradeoffs in the recognition process, a system is implemented using a representation based on significant contour curvature changes and a recognition engine based on geometric constraints of feature properties. Examples of the system's performance are given, followed by an analysis of the results. In conclusion, the system's benefits and limitations are presented.

UV Embossed Plastic Chip for Protein Separation and Identification

This report demonstrates a UV-embossed polymeric chip for protein separation and identification by Capillary Isoelectric Focusing (CIEF) and Matrix Assisted Laser Desportion/Ionization Mass Spectrometry (MALDI-MS). The polymeric chip has been fabricated by UV-embossing technique with high throughput; the issues in the fabrication have been addressed. In order to achieve high sensitivity of mass detection, five different types of UV curable polymer have been used as sample support to perform protein ionization in Mass Spectrometry (MS); the best results is compared to PMMA, which was the commonly used plastic chip for biomolecular separation. Experimental results show that signal from polyester is 12 times better than that of PMMA in terms of detection sensitivity. Finally, polyester chip is utilized to carry out CIEF to separate proteins, followed by MS identification.