24 August 1999 Automatic detection and recognition of stationary motorized vehicles in infrared images
Author Affiliations +
Abstract
This paper presents an algorithmic approach for the automatic detection and recognition of stationary motorized vehicles in infrared images. Covering the whole object recognition processing chain, robust solutions are proposed for the preprocessing, detection and segmentation steps, with particular emphasis on the feature extraction and final classification stages. The segmentation process consists of a graph based analysis strategy that group high level features such as hot regions and contour segments of pre-specified types into bounding rectangles of the potentially relevant objects. Feature extraction proceeds with the superimposition of a grid of a predefined number of equally sized cells onto the bounding rectangular window determined for each potential target. From the measurements evaluated for each cell it is built a feature vector that feeds a supervised neural network classifier, aiming to perform a coarse recognition of the detected targets.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bento A. Brazio Correia, Joao Dinis, Roger Davies, "Automatic detection and recognition of stationary motorized vehicles in infrared images", Proc. SPIE 3718, Automatic Target Recognition IX, (24 August 1999); doi: 10.1117/12.359944; https://doi.org/10.1117/12.359944
PROCEEDINGS
12 PAGES


SHARE
Back to Top