Dynamical Pattern Vector in Pattern Recognition with the Use of Thermal Images

Zygmunt Kuś,M Kavakli,M Pal,M.A.B.M Basri,A Amini,S.C.H Li,M.J.E Salami,A.B Masli

doi:10.1051/matecconf/20165602010

Abstract

The goal of the following paper was to develop the methodology of object tracking in adverse conditions. Suddenly appearing clouds, fog or smoke could be the examples of atmospheric conditions. We used thermal and visible images in each moment during object tracking. We computed the pattern vectors of the tracked object on the basis of the visual and thermal images separately. The pattern vector and current feature vector for an image of a given type are used to compute the distance between the object pattern vector and feature vector calculated for a given location of the aperture. It is calculated for both: the visual and thermal image. The crux of the proposed method was the algorithm of selection which distance (for visual or thermal image) was used for object tracking. It was obtained by multiplying the values of the distances between a pattern vector and current feature vector by some coefficients (different for thermal and visual images). The values of these coefficients depended on the usefulness of a given type of an image for pattern recognition. This usefulness was defined by the variability of the particular pixels in the image which is represented by calculating gradient in the image. On top of that, this study presented the examples of the object recognition by means of the developed method.

Highlights

Thermal imagery, which is obtained from an infrared sensor and can display invisible thermal energy emitted from objects, is a crucial source of information in low visibility conditions
The paper has developed the methodology of object tracking in adverse conditions
The obtained results could be used for other disturbances such as suddenly appearing clouds, fog or adverse atmospheric conditions

Summary

Introduction

Thermal imagery, which is obtained from an infrared sensor and can display invisible thermal energy emitted from objects, is a crucial source of information in low visibility conditions. This information can be very useful for image processing system which is used for surveillance, object tracking or security applications. We will consider the problem of object tracking and pattern recognition in the conditions of distorted visibility of the object. We assume that both visual and thermal images can be sometimes distorted. The process of pattern recognition is based on this part of the pattern vector for which the image is not disturbed

The Basic Assumptions of Pattern Recognition

The Algorithm of the Use of the Dynamical Features Vector

Examples

Conclusions