Person:
Ferri, Bonnie H.

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Author: Yezzi, Anthony ×

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    A Real-Time Curve Evolution-Based Image Fusion Algorithm for Multisensory Image Segmentation
    (Georgia Institute of Technology, 2003-04) Ding, Yuhua ; Vuchtsevunos, George J. ; Yezzi, Anthony ; Daley, Wayne ; Ferri, Bonnie H.
    A partial differential equation (PDE)-based feature-level image fusion approach is proposed for multisensory image segmentation. The energy functional of the proposed fusion model is a weighted sum of several functionals, each constructed based on the characteristics of the sensor image. The weight selection decides the way that the model handles redundant, conflicting, or complementary information involved in the multisensory data. The method is implemented using level sets and is fast enough for real-time segmentation tasks. Finally the algorithm is applied to the segmentation of x-ray and visual images, and the results show that the fusion algorithm is efficient, accurate, and robust.
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    A Real-Time Curve Evolution-Based Image Fusion Algorithm for Multisensory Image Segmentation
    (Georgia Institute of Technology, 2003-04) Ding, Yuhua ; Vuchtsevunos, George J. ; Yezzi, Anthony ; Daley, Wayne ; Ferri, Bonnie H.
    A partial differential equation (PDE)-based feature-level image fusion approach is proposed for multisensory image segmentation. The energy functional of the proposed fusion model is a weighted sum of several functionals, each constructed based on the characteristics of the sensor image. The weight selection decides the way that the model handles redundant, conflicting, or complementary information involved in the multisensory data. The method is implemented using level sets and is fast enough for real-time segmentation tasks. Finally the algorithm is applied to the segmentation of x-ray and visual images, and the results show that the fusion algorithm is efficient, accurate, and robust.
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    Fusion of Visible and X-Ray Sensing Modalities for the Enhancement of Bone Detection in Poultry Products
    (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.