Research Article Open Access

DETECT EXPLOSIVES BY INFRARED IMAGERY USING MERGING ANOMALY ALGORITHM AND IMAGE FEATURES

Abstract

A innovative tactic method used for Merging Different Anomaly Algorithm decisions with image space cell-structured features on a long wave infrared (LWIR) System with context of forward Looking (FL) buried explosive hazard detection along a road.A pre-screener is begin,widely helps to produce ensemble of trainable size contrast filters focusing in Universal Transverse Mercator(UTM) Space .Next,Features from different algorithm are mined from UTM confidence map along with average shift grouping in Universal Transverse Mercator (UTM) space. Features available in image chips demonstrating anomaly decisions from different algorithms are extracted from UTM confidence maps based on maximally stable extremal regions (MSERs) and Guassian mixture models(GMMs).Pre-scanner hits in UTM space are back projected into the video at multiple standoff distance and cell-Structured Local Binary Patterns(LBPs), Histogram of Gradients(HOGs) and Mean-variance descriptors are extracted. Experiments are conducted using Buried Volatiles with varying metal contents and depths in U.S.Army Test site. Results are extremely encouraging in FL imaging and show a significant decrease in the number of false alarms(Fas). Targests not currently detected by our system are also not detected by a manually under human visualization inspections

MS.F.FATHIMA

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