Edge-texture wavelet features for automated x-ray inspection

Harold H. Szu; Charles C. Hsu

doi:10.1117/12.271738

3 April 1997 Edge-texture wavelet features for automated x-ray inspection

Harold H. Szu, Charles C. Hsu

Proceedings Volume 3078, Wavelet Applications IV; (1997) https://doi.org/10.1117/12.271738
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

Computer aided target recognition (ATR) is introduced to reduce the false alarm rate (FAR) based on a pair of x-ray images. We assume that a homogeneous texture feature persists throughout the area of interest (AOI) in cases of contraband drug substances. We introduce an adaptive edge- texture wavelet transform (WT) in order to match the substance texture. Furthermore, we introduce a feature persistence measure in terms of a multi-resolution fractal dimension analysis. Results of an FPM plotted against the size of the box region show that the reflectance AOI is similar to the false contraband; but that of actransmitted AOI reveals a different fractal dimension between the positive and negative contrabands. Thus we can reduce the FAR.

Citation Download Citation

Harold H. Szu and Charles C. Hsu "Edge-texture wavelet features for automated x-ray inspection", Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); https://doi.org/10.1117/12.271738

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