Evaluation Of Automatic Target Recognition Algorithms

In this paper we briefly review the techniques used to solve the automatic target recognition (ATR) problem. Emphasis is placed on the algorithmic and implementation approaches. The evaluation of ATR algorithms such as target detection, segmentation, feature evaluation and classification are discussed in detail and several new quantitative criteria are suggested. The evaluation approach is discussed and various problems encountered in the evaluation of algorithms are addressed. Strategies to be used in the data base design are outlined. New techniques such as the use of semantic and structural information, hierarchical reasoning in the classification and incorporation of multisensor in the ATR systems are also presented.

[1]  Richard D. Holben Moving Target Identification (MTI) Algorithm For Passive Sensors , 1980, Photonics West - Lasers and Applications in Science and Engineering.

[2]  A. Rosenfeld,et al.  Segmentation of FLIR Images: A Comparative Study , 1982 .

[3]  D. F. Barbe,et al.  VHSIC Systems and Technology , 1981, Computer.

[4]  Douglas F. Elliott,et al.  Moving Target Tracking Using Symbolic Registration , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  F.W. Smith,et al.  Automatic Ship Photo Interpretation by the Method of Moments , 1971, IEEE Transactions on Computers.

[6]  P. M. Narendra,et al.  Prototype Automatic Target Screener , 1979, Other Conferences.

[7]  Belur V. Dasarathy Information Processing For Target Recognition From Autonomous Vehicles , 1980, Photonics West - Lasers and Applications in Science and Engineering.

[8]  Jack Sklansky,et al.  The Detection and Segmentation of Blobs in Infrared Images , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[9]  C. H. Chen,et al.  Object isolation in FLIR images using Fisher's linear discriminant , 1982, Pattern Recognit..

[10]  King-Sun Fu,et al.  Automatic classification of cervical cells using a binary tree classifier , 1983, Pattern Recognition.

[11]  Alton L. Gilbert,et al.  Video Data Conversion and Real-Time Tracking , 1981, Computer.

[12]  Mark L. Burton,et al.  Comparison Of Imaging Infrared Detection Algorithms , 1982, Optics & Photonics.

[13]  O. Robert Mitchell,et al.  Segmentation And Classification Of Targets In Flir Imagery , 1979, Optics & Photonics.

[14]  Chun Moo Lo Forward Looking Infrared (FLIR) Image Enhancement For The Automatic Target Cuer System , 1980, Optics & Photonics.

[15]  Azriel Rosenfeld,et al.  Algorithms and Hardware Technology for Image Recognition , 1976 .

[16]  Bir Bhanu,et al.  Recognition of Occluded Objects , 1983, International Joint Conference on Artificial Intelligence.

[17]  Olivier D. Faugeras,et al.  Segmentation of Images Having Unimodal Distributions , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Bir Bhanu,et al.  Intelligent Autocueing Of Tactical Targets , 1984, Optics & Photonics.

[19]  E. M. Rounds,et al.  Feature Extraction From Forward Looking Infrared (FLIR) Imagery , 1980, Optics & Photonics.

[20]  Ernesto Bribiesca,et al.  How to describe pure form and how to measure differences in shapes using shape numbers , 1980, Pattern Recognit..

[21]  Michael K. Giles,et al.  A Real-Time Video Tracking System , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.