(Georgia Institute of Technology, 2002)
Ding, Yuhua; Vachtsevanos, George J.; Yezzi, Anthony; Zhang, Yingchuan; Wardi, Yorai Y.
Segmentation accuracy is shown to be a critical factor in
detection rate improvement. With accurate segmentation,
results are easier to interpret, and classification
performance is better. Therefore, it is required to have a
performance measure for segmentation evaluation.
However, a number of restrictions limit using existing
segmentation performance measures. In this paper a recursive segmentation and classification scheme is proposed to improve segmentation accuracy and
classification performance in real-time machine vision applications. In this scheme, the confidence level of
classification results is used as a new performance
measure to evaluate the accuracy of segmentation
algorithm. Segmentation is repeated until a classification
with desired confidence level is achieved. This scheme can be implemented automatically. Experimental results
show that it is efficient to improve segmentation accuracy
and the overall detection performance, especially for
real-time machine vision applications, where the scene is
complicated and a single segmentation algorithm cannot
produce satisfactory results.
(Georgia Institute of Technology, 2000)
Vachtsevanos, George J.; Daley, Wayne D.; Ferri, Bonnie H.; Yezzi, Anthony; Ding, Yuhua
The 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.