Object shape extraction from cluttered bags

Nikolay Metodiev Sirakov

doi:10.1117/12.2268810

1 May 2017 Object shape extraction from cluttered bags

Nikolay Metodiev Sirakov

Proceedings Volume 10202, Automatic Target Recognition XXVII; 102020P (2017) https://doi.org/10.1117/12.2268810
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

The passengers flow at the US airports increased in the recent years. The larger number of passengers demands for lower number of false alarms and higher accuracy of threat detection at the time of baggage screening. This paper presents an algorithm to detect and extract possible explosive containers in X-Ray- CT bags images. The algorithm is composed by three main stages. The 1st one makes the threat container excels among the other objects in the bag image. The 2nd approach: Extracts the SURF features from the query and the bag images; Matches the SURF feature vectors from the two images. The bag image points (pixels), at which the best match is found, define regions of interest (RoI). Different RoI in a bag are identified by separate clusters of points. At the 3rd stage of the algorithm an enlarging active contour (AC) extracts the boundary of every RoI. The starting point of every AC is the mass center of the corresponding cluster of SURF points. The theory is validated on a number of X-ray/CT images. A qualitative comparison with contemporary methods outlines the advantages and the contribution of the present algorithm.

Citation Download Citation

Nikolay Metodiev Sirakov "Object shape extraction from cluttered bags", Proc. SPIE 10202, Automatic Target Recognition XXVII, 102020P (1 May 2017); https://doi.org/10.1117/12.2268810

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available