Morphological wavelet transform for distortion-invariant object detection in clutter

Anqi Ye; David P. Casasent

doi:10.1117/12.170054

15 March 1994 Morphological wavelet transform for distortion-invariant object detection in clutter

Anqi Ye, David P. Casasent

Proceedings Volume 2242, Wavelet Applications; (1994) https://doi.org/10.1117/12.170054
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

We developed an approach combining morphological processing and wavelet transforms to detect multiple objects in an input scene. The input scene contains different types of background clutter regions and multiple objects in different classes, with different object aspect views, different object representations, hot/cold/bimodal/partial object variations, and high/low object contrast variations. Our approach provides high detection rates and low false alarm rates. The most computationally demanding operations required are realizable on an optical correlator.

Citation Download Citation

Anqi Ye and David P. Casasent "Morphological wavelet transform for distortion-invariant object detection in clutter", Proc. SPIE 2242, Wavelet Applications, (15 March 1994); https://doi.org/10.1117/12.170054

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