Multi-Classifier Buried Mine Detection Using MWIR Images

1. Defense and Security Symposium 2007 Multi-Classifier Buried Mine Detection Using MWIR Images April 10, 2007 Mr. Anh H. Trang Mr. Chung Phan US Army RDECOM Dr. Bo Ling Migma Systems, Inc.

2. Presentation Outline - Overall Technical Approach - MWIR Image Thresholding and Clustering - Buried Mine Directional Signatures - Multi-Classifier for Buried Mine Detection - Test Results - Conclusion

3. Overall Approach Image Buried Mine Buried Mine Classifier (horizontal) Image Thresholding Buried Mine Classifier (vertical) Fusion Image Clustering Image Windowing Buried Mine Classifier (diagonal)

4. Image Thresholding Using Wavelet Transform Image Thresholding Based on Inverse Wavelet Transform where is related to the inverse of discrete wavelet transform, th, tv , and td are the threshold values associated with three decompositions in the wavelet domain.

5. Image Thresholding Original Image Thresholded Image Thresholding method has preserved the surface and buried mines.

6. Image Clustering Image BuriedMine Buried Mine Classifier (horizontal) Image Thresholding Buried Mine Classifier (vertical) Fusion Image Clustering Image Windowing Buried Mine Classifier (diagonal)

7. Adaptive Self-Organizing Maps (ASOM) Neuron activation function Data Similarity Measurement neurons No prior knowledge of number of clusters

8. Clustering after Thresholding Thresholded Image Clusters Clustering Each cluster represents a potential mine

9. Buried Mine Signatures Original Image Target Chip Clusters The similarity-based 3D ASOM is used to find clusters in the windowed target chip.

10. Directional Scanning We build buried mine signatures in three directions Horizontal Scan Vertical Scan Diagonal Scan

11. Library of Buried Mine Signatures We have found that the thermal variation patterns exhibited in daytime and nighttime are significantly different.

12. Signature Vectors Vertical Signature Diagonal Signature Horizontal Signatures

13. Example of Buried Mine Signatures Target Chip Signature Histogram The signatures associated with buried mines are common in - Long vector length - Histogram peaked in the middle

14. Signature Comparison Mine Signatures

15. False Alarm Mitigation Signature difference can be used to eliminate false alarms.

16. Multi-Classifier Detection Image Buried Mine Buried Mine Classifier (horizontal) Image Thresholding Buried Mine Classifier (vertical) Fusion Image Clustering Image Windowing Buried Mine Classifier (diagonal)

17. Three Directional Classifiers Diagonal Classifier Each of three classifiers will process the corresponding directional signatures. Horizontal Classifier Vertical Classifier

18. Test Result of Nighttime Image Original Image We have tested both daytime and nighttime images taken from MWIR data collected as part of Lightweight Airborne Multispectral Minefield Detection (LAMD) program.

19. Test Result - Clustering Original Image Clustered Image Since each cluster could represent a buried mine, we must process all clusters.

20. Test Result - Three Classifiers Each cluster is windowed and processed by all three directional classifiers. There are three independent detection results. Three false alarms Three false alarms Four false alarms

21. Test Result - Fusion We have used a simple fusion scheme: a buried mine is declared only if it is detected by all three classifiers. One advantage of this type of fusion is low false alarm rate since three classifiers may not report the same false detection in the same image.

22. Final Detection They can be further eliminated. Two false alarms left.

23. Conclusion For each target chip, we scan it in three directions: vertical, horizontal, and diagonal to construct three signatures. For the same target chip, there will be a total of three classifiers associated with vertical, horizontal, and diagonal scans. These three classifiers are applied to the same target chip, resulting in three independent detection results, which are further fused for a refined detection. New results will be reported in the future once we test the system with new images.