Prof. David Casasent

Headshot of David Casasent

Laboratory for Optical Data Processing
Department of Electrical and Computer Engineering

Carnegie Mellon University
Pittsburgh, PA 15213-3890
Telephone 412.268.2464; Fax 412.268.6345

casasent AT ece DOT cmu DOT edu

[ECE Faculty Page]


Hamerschlag Hall, B202

Administrative Assistant:

Marilyn L. Patete marilynp AT andrew DOT cmu DOT edu

Hamerschlag Hall B211, (Voice) 412-268-8162, (Fax) 412-268-6345

Research Interests:

Image processing, distortion-invariant detection and pattern recognition

Target recognition, robotic vision, product inspection, biometric recognition

Neural networks, support vector machines, morphological, and distortion-invariant filters

Nonlinear algorithm fusion to improve PD and PFA

Synthetic aperture radar, IR and EO object detection and recognition

Hyperspectral product inspection




Current Projects


Product Inspection - We are developing non obtrusive methods to locate anomalies in various products (e.g. locating tumors in chicken carcasses), using hyperspectral data.

Automatic Target Recognition using Distortion Invariant Filters We locate objects or regions of interest (ROIs) in a scene; the objects can be at any orientation, contrast or class, and in IR, EO or SAR imagery.


Face Recognition using Correlation Filters We are developing face recognition systems that are invariant to illumination, pose and expression variations using various distortion invariant filters.


Fingerprint Recognition-We have developed elastic distortion-invariant correlation filters for live-scan fingerprint matching.



Biometric Fusion We are developing novel fusion methods which combine face and fingerprint biometric results using fingerprint data quality information, which outperforms standard multimodal results and unimodal systems.


Support Vector Machines and Neural Networks- We use support vector machines and neural networks for a wide variety of applications ranging from automatic target recognition( ATR) to biometric identification.









Select Publications:

David Casasent and Yu-Chiang Wang, A Hierarchial Classifier Using New Support Vector Machines for Automatic target Recognition , Neural Networks Special Issue, July 2005,pp 541-548

Rohit Patnaik and David Casasent, MINACE filter classification algorithms for ATR using MSTAR data, Proc. SPIE, vol. 5807, pg 100-111,April 2005

Rohit Patnaik and David Casasent, Illumination invariant face recognition and impostor rejection using different MINACE filter algorithms, Proc of SPIE, vol. 5816, April 2005,pp 94-105

Chao Yuan and David Casasent, Face Recognition and Verification with Pose and Illumination Variations and Impostor Rejection, keynote address, , Proc of SPIE, vol. 5779, April 2005,pg 247-255

Craig Watson and David Casasent, Recognition of live-scan fingerprints with elastic distortions using correlation filters, Optical Engineering, October 2004, pp 2274-2282

David Casasent and Xue-Wen Chen, Waveband selection for hyperspectral data: optimal feature selection, Proc of SPIE 5106, October 2003, pp 259-270


Songyot Nakariyakul and David Casasent, Hyperspectral Feature Selection and Fusion for Detection of Chicken Skin Tumors , Proc of SPIE 5271, October 2003, pp 128-139


Songyot Nakariyakul and David Casasent, Hyperspectral Ratio Feature Selection: Agricultural Product Inspection Example, Proc of SPIE 5587, October 2004, pp 133-143


Selected algorithm code:

Adaptive branch and bound feature selection algorithm (created by Songyyot Nakariyakul): ABB


Research Description

Vita: Post Script format

Resume: pdf format Postscript

Current Teaching

18-793 Optical Image and Radar Processing (Spring)

18-551 Digital Communications and Signal Processing Systems Design (Fall)


Current graduate students:

  • Songyot Nakariyakul, snakariy AT andrew DOT cmu DOT edu
  • Rohit Patnaik, rpatnaik AT cmu DOT edu
  • Yu-Chiang Wang, ycwang AT cmu DOT edu
  • Chao Yuan
  • Avinash Nehemiah, avinash AT cmu DOT edu

Last updated October 2005