Robust Recognition of Ship Types from an Infrared Silhouette
Rowe, Neil C.
MetadataShow full item record
Accurate identification of unknown contacts crucial in military intelligence. Automated systems that quickly and accurately determine the identity of a contact could be a benefit in backing up electronic-signals identification methods. This work reports two experimental systems for ship classification from infrared FLIR images. In an edge-histogram approach, we used the histogram of the binned distribution of observed straight edge segments of the ship image. Some simple tests had a classification success rate of 80% on silhouettes. In a more comprehensive neural-network approach, we calculated scale-invariant moments of a silhouette and used them as input to a neural network. We trained the network on several thousand perspectives of a wire-frame model of the outline of each of five ship classes. We obtained 70% accuracy with detailed tested on real infrared images but performance was more robust than with the edge-histogram approach.
This paper appeared in the Command and Control Research and Technology Symposium, San Diego, CA, June 2004.
Showing items related by title, author, creator and subject.
Erwert, Jonathan P. (Monterey, CA; Naval Postgraduate School, 2018-12);Traditional signature-based malware detection is effective, but it can only identify known malicious programs. This thesis attempts to use machine-learning techniques to successfully identify previously unknown malware ...
Borges, C.F. (1999);We examine the histogram method proposed in  for estimating the parameters associated with a Markov random field. This method relies on the estimation of the local interaction sums from histogram data. We derive an ...
Richstein, James K. (Monterey, California. Naval Postgraduate School, 1993-12);Histogram generation, a standard image processing operation, is a record of the intensity distribution in the image. Histogram generation has straight forward implementations on digital computers using high level languages. ...