Knowledge-based hierarchical region-of-interest detection

Huibao Lin, Jennie Si, Glen P. Abousleman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Detecting regions of interest (ROIs) in a complex image is a critical step in many image processing applications. In this paper, we present a new algorithm that addresses several challenges in ROI detection. The novelty of our algorithm includes: (i) every ROI contains one and only one object; (ii) the detected ROIs can have irregular shapes as opposed to the rectangular shapes that are typical of other algorithms; (iii) the algorithm is applicable to images that contain connected objects, or when the objects are broken into pieces; (iv) the algorithm is not sensitive to contrast levels in the image, and is robust to noise. These characteristics make the proposed algorithm applicable to low-resolution, real-world imagery without costly post-processing. The proposed algorithm is shown to provide outstanding performance with low-quality imagery, and is shown to be fast and robust.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
StatePublished - 2002
Event2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL, United States
Duration: May 13 2002May 17 2002

Other

Other2002 IEEE International Conference on Acoustic, Speech, and Signal Processing
CountryUnited States
CityOrlando, FL
Period5/13/025/17/02

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics

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  • Cite this

    Lin, H., Si, J., & Abousleman, G. P. (2002). Knowledge-based hierarchical region-of-interest detection. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 4)