You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
13 April 2009Neural network target identification system for false alarm reduction
A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with
adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest.
Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum
Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then
eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature
extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back
propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This
paper discusses the test of the system performance and parameter optimizations process which adapts the system to
various targets and datasets. The test results show that the system was successful in substantially reducing the false
positive rate when tested on a sonar image dataset.
The alert did not successfully save. Please try again later.
David Ye, Weston Edens, Thomas T. Lu, Tien-Hsin Chao, "Neural network target identification system for false alarm reduction," Proc. SPIE 7340, Optical Pattern Recognition XX, 73400K (13 April 2009); https://doi.org/10.1117/12.820949