A Methodology for the Development of Machine Vision Algorithms Through the use of Human Visual Models

The development of machine vision algorithms for inspection and machine guidance has traditionally relied on the knowledge and experience of the developers as most of the techniques are based on heuristics and trial and error. This is especially problematic in the area of natural products where variability of the products is the rule rather than the exception. Humans are particularly good in functioning in this arena and in this thesis we look at the development of techniques derived from the functions of the human visual system (HVS). We first identify the significant processes in the HVS and highlight those that we believe are germane to the problems of interest. We then develop computational techniques using these methods and demonstrate their applicability to practical problems. This thesis uses the knowledge that the HVS is considered to consist of three sequential operations (sensing; encoding/transfer; and image interpretation) as a basis for developing a parallel procedure for a machine vision system. We have found that outputs derived from a simulation of the behaviors of receptive fields in the retina and in the higher levels of the brain can generate useful and robust features. Equivalent processes are then developed for machine applications under the guidance of a human operator to identify the areas of interest in the scene for the problem under consideration. Specifically we use the processes for encoding/transfer of data from the retina to develop techniques to enhance color contrasts, and compute color image features that are useful for defect detection and identification in real world images. This is accomplished by a transformation from image space to a characteristic response space that improves the robustness of classification. In this thesis the approach developed is applied to two industrial problems in the quality monitoring of meat and vegetables. The first problem concerns the quality monitoring of breast butterflies and the other the detection of defects on the surface of citrus. The approach is shown to derive algorithms that are robust and can be implemented at high rates of speed. Additionally we also identify a model within which further developments can be conducted as we learn more about the functioning of the HVS.Ph.D.Committee Chair: Dr. Kok-Meng Lee; Committee Member: Dr. Bert Bras; Committee Member: Dr. Paul Griffin; Committee Member: Dr. Suresh Sitaraman; Committee Member: Dr. Ted Dol

Structural genomics target selection for the New York consortium on membrane protein structure

The New York Consortium on Membrane Protein Structure (NYCOMPS), a part of the Protein Structure Initiative (PSI) in the USA, has as its mission to establish a high-throughput pipeline for determination of novel integral membrane protein structures. Here we describe our current target selection protocol, which applies structural genomics approaches informed by the collective experience of our team of investigators. We first extract all annotated proteins from our reagent genomes, i.e. the 96 fully sequenced prokaryotic genomes from which we clone DNA. We filter this initial pool of sequences and obtain a list of valid targets. NYCOMPS defines valid targets as those that, among other features, have at least two predicted transmembrane helices, no predicted long disordered regions and, except for community nominated targets, no significant sequence similarity in the predicted transmembrane region to any known protein structure. Proteins that feed our experimental pipeline are selected by defining a protein seed and searching the set of all valid targets for proteins that are likely to have a transmembrane region structurally similar to that of the seed. We require sequence similarity aligning at least half of the predicted transmembrane region of seed and target. Seeds are selected according to their feasibility and/or biological interest, and they include both centrally selected targets and community nominated targets. As of December 2008, over 6,000 targets have been selected and are currently being processed by the experimental pipeline. We discuss how our target list may impact structural coverage of the membrane protein space

Fusion of Visible and X-Ray Sensing Modalities for the Enhancement of Bone Detection in Poultry Products

©2000 SPIE - Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.Presented at Biological Quality and Precision Agriculture II, November 05, 2000, Boston, MA.http://dx.doi.org/10.1117/12.411744The U.S. demand for deboned chicken has risen greatly in the past 5 years, with the expectations that this demand will oniy continue at an accelerated level. The standard inspection process for bones in meat is for workers to manually feel for bones. It is clear that this time-consuming manual inspection method is insufficient to meet the increasing demand for deboned meat products. Georgia Tech Electrical Engineering faculty and Research Scientists in conjunction with a leading x-ray equipment manufacturer are working together on the development of a system to fuse information from visible images and x-ray images to enhance the accuracy of detection. Currently there are some bones that x-ray systems have difficulty detecting. These are usually relatively thin and are located near the surface of the meat. A primary example is a fanbone (so called because of its shape). We will describe and present results from work geared towards the development of an integrated system that would fuse visible and x-ray information. Significant benefits to the poultry industry are anticipated in terms of reduced processing costs, improved inspection performance and increased throughput through the use of the integrated system to be described. Additionally, generic aspects of the proposed technologies may be applicable to other food processing industries

The Effects of Emotional Support on Perceived Job Stress and Strain

This article uses a national sample of social workers to examine the relationship between work stress, strain, and emotional support. These results indicate negative associations between support and perceived stress and strain. The authors, however, found no evidence for the buffering effects of emotional support. The authors discuss the implications of these findings.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67373/2/10.1177_002188638402000205.pd

Chronology and Statistics : Objective Understanding of Authorial Meaning

This paper is an attempt to prove that chronology and statistics are the effective means for objective interpretation of authorial meaning. In defence of his hermeneutic theory against Eagleton’s liberal-humanistic opposition, Hirsch asserts no other object can be the norm of literary criticism than authorial meaning. One of the most useful tools for the objective detection of authorial meaning is the Sanger-Kroeber method—Sanger’s chronological study of the structure of fiction and Kroeber’s statistical quantification of formal elements. Its application to the analysis of Elizabeth Gaskell’s Mary Barton reveals that the novel’s central protagonist is the eponymous heroine, not her father as has been conventionally considered. Subjective readings will be superseded by new ones. But, readings based on objective data will not