Automatic small target detection in synthetic infrared images

Date

2017-04-11

Author

YARDIMCI, Ozan
Ulusoy, İlkay

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

197
views

0
downloads

Automatic detection of targets from far distances is a very challenging problem. Background clutter and small target size are the main difficulties which should be solved while reaching a high detection performance as well as a low computational load. The pre-processing, detection and post-processing approaches are very effective on the final results. In this study, first of all, various methods in the literature were evaluated separately for each of these stages using the simulated test scenarios. Then, a full system of detection was constructed among available solutions which resulted in the best performance in terms of detection. However, although a precision rate as 100% was reached, the recall values stayed low around 25-45%. Finally, a post-processing method was proposed which increased the recall value while keeping the precision at 100%. The proposed post-processing method, which is based on local operations, increased the recall value to 65-95% in all test scenarios.

Subject Keywords

Automatic target detection, Small target detection, Infrared image

URI

https://hdl.handle.net/11511/43420

DOI

https://doi.org/10.1117/12.2263616

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Automatic small target detection in infrared images of various backgrounds from various distances Yardımcı, Ozan; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2015) Automatic detection of small targets in various backgrounds from far distances is a very challenging problem. Background clutter and small target size are the main difficulties which should be solved while reaching a very high detection performance as well as a very low computational load. In this thesis, various methods such as Top-Hat and Wavelet Transform, edge, filtering, saliency and feature based algorithms are investigated. All of the methods are compared using some realistic test scenarios, which ar...
Low velocity moving target detection with synthetic aperture radar Narin, Görkem; Koç, Seyit Sencer; Department of Electrical and Electronics Engineering (2019) Detection of slow moving targets with small radar cross sections (RCS) is a challenging problem for the Ground Moving Target Indication (GMTI) systems. GMTI systems face high false alarm and/or frequent target miss rates for such targets. Synthetic Aperture Radar (SAR) systems, on the other hand, offer sufficiently large target energy return, unfortunately not localized to a point in the SAR image due to target motion. This thesis is focused on the study of two methods for moving target detection in SAR ima...
Investigation of the Effects of Buried Object Orientation in Subsurface Target Detection by GPR Doğan, Mesut; Sayan, Gönül (2017-10-27) Use of ultra-widehand ground penetrating radars (GPRs) have been the most effective approach in subsurface target detection. Proper preprocessing, prescreening, feature extraction, classification and fusion techniques are all needed to satisfy the requirements of high detection probability and low false alarm rates, simultaneously. Dominating ground reflection signals and soil clutter effects including the randomly varying non-planar ground surfaces, inhomogeneous soil nature, pebbles or rocks within the so...
Small Target Detection By Morphological Operations Yardimci, Ozan; Tunc, Seyit; Ulusoy, İlkay (2015-05-19) Automatic target detection has an important application field in today's missile technology. Therefore, there are many studies in this field. In this context, morphological operation (MO) based methods were firstly investigated and tested on the prepared scenarios. As a results of test results, methods were compared on the basis of the detection performance, user defined parameter quantity and processing time. After comparison results, the methods are determined which has better detection performance, do no...
A variable structure - autonomous - interacting multiple model ground target tracking algorithm in dense clutter Alat, Gökçen; Leblebicioğlu, Mehmet Kemal; Department of Electrical and Electronics Engineering (2013) Tracking of a single ground target using GMTI radar detections is considered. A Variable Structure- Autonomous- Interactive Multiple Model (VS-A-IMM) structure is developed to address challenges of ground target tracking, while maintaining an acceptable level computational complexity at the same time. The following approach is used in this thesis: Use simple tracker structures; incorporate a priori information such as topographic constraints, road maps as much as possible; use enhanced gating techniques to ...

Citation Formats

O. YARDIMCI and İ. Ulusoy, “Automatic small target detection in synthetic infrared images,” 2017, vol. 10202, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43420.