Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition Accuracy

Transcription

1 January 31, 2007 Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition Accuracy Severin Kampl, Austria Visual Communications and Image Processing 2007, San Jose Convention Center, California

2 Authors Carinthia Tech Institute, University of Applied Sciences, Austria Department of Computer Sciences, Salzburg University, Austria Michael Dorfer Alexander Maier Andreas Palli Andreas Uhl Severin Kampl Daniel Mark Günter Scheer # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 2/22

3 Presentation Structure 1 Introduction 2 Experimental Studies 3 Results 3.1 Results of Fingerprints 3.2 Results of Faceprints 4 Conclusion # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 3/22

4 1 Introduction Boom of Biometric Systems How to store the acquired sensor data? # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 4/22

5 1 Introduction Motivation of Compression Storage of Reference Data Storing only extracted features (+): smaller amount of data (-): Re-Enrollment in case of replacement Storing the original sensor data (+): more flexible (-): large amount of data compression technology # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 5/22

6 1 Introduction Motivation of Compression Transmission after sensor data acquisition Acquisition stage dislocated from matching stage Transfer over a wireless network link compression technology # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 6/22

7 1 Introduction Compression Technology Lossy techniques (+): Maximizes benefit (-): Artifacts could interfere FRR and FNMR will increase FAR and/or FMR might be affected Our Focus: lossy compression of fingerprint and face images # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 7/22

8 1 Introduction Fingerprints Characteristics High energy in high frequency bands WSQ standard adopted by the FBI Superior to JPEG Further Wavlet based approaches Only a few studies about matching rates of Biometric Systems available # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 8/22

9 Typical average image data Most engergy in low and medium bands No specific compression format needed JPEG and JPEG Introduction Characteristics of Faceprints # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 9/22

10 2 Experimental Study Experimental Setup PSNR original image compression comp. image Biometric System MATCHING RESULT general purpose compression impact on recognition accuracy rate distortion performance calculate C.R. Final goal: ranking of compression schemes # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 10/22

11 Sample Data: 2 Experimental Study Settings and Methods 256 x 256 pixel 8bpp (grayscale( grayscale) Fingerprints from sample database Frontal faces from several databases # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 11/22

12 3.1 Average Rate Distortion Performance over all Images all Averages PSNR across all images JPEG2000 and SPIHT behave similar VQ and JPEG equivalent up to 20 c.r. Poor results: fractal compression Note: Absolute PSNR values are rather low Not easy to compress # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 12/22

13 3.1 VeriFinger results (averaged) all JPEG superior JPEG superior at c.r.. = 10 Overall: JPEG2000 and SPIHT outperform others # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 13/22

14 3.1 efinger results (averaged) all JPEG2000, SPIHT, VQ corresponding to PSNR JPEG below Vector Quantization Fractal compression delivers poor results # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 14/22

15 3.1 FiRS results (averaged) all Similar to efinger System (note( note: : y is distance) # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 15/22

16 3.1 Conclusion of the Fingerprint section PSNR is satisfying, but not perfect Top ranked algos exhibit top performance Fractal compression obviously not suited Vector Quantization does suprisingly well, superior to JPEG in contrast to PSNR values JPEG at low compression ratios performs well JPEG2000 SPIHT 1 VQ, JPEG 2 Fractal 3 # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 16/22

17 3.2 Average Rate Distortion Performance over all Face Images ALL PSNR values significantly higher SPIHT outperforms JPEG2000 by ~0.5dB Vector Quantization is ranked 3rd Fractal is superior JPEG at low bitrates # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 17/22

18 3.2 Averaged (over all images) VeriLook results ALL JPEG > Fractal compression (below 40 c.r.).) JPEG > Vector Quantization (below 20 c.r.).) VQ slight above JPEG2000 (in contrast to PSNR) # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 18/22

19 3.2 Averaged (over all images) FaRS results ALL Score corresponds to PSNR values for JPEG2000, SPIHT, PRVQ JPEG does well compared to ist PSNR values Fractal compression performs worse, unlike at PSNR # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 19/22

20 3.2 Conclusion of the Face image section PSNR is a less reliable indicator for face recognition Although face images exhibits more common properties JPEG s performance in face recognition systems is underestimated when looking at PSNR only Similar to fingerprinting Fractal Compression is the least suited algorithm Like PSNR values predict,, JPEG2000 and SPIHT perform well # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 20/22

21 4 General Conclusion PSNR is a good indicator for wavelet based compression algorithms and predicts poor scores of Fractal Compression Face images: JPEG performs better than Fractal at high and medium bitrates JPEG2000, SPIHT, VQ are suitable JPEG and Fractal Compression could affect parameters # : Comparison of Compression Algorithms Impact on Fingerprint and Face Recognition 21/22

22 Thank you for your Attention! Severin Kampl on behalf of: Michael Dorfer,, Alexander Maier, Daniel Mark, Andreas Palli, Günter Scheer, Univ.-Prof. Mag. Dr. Andreas Uhl