PErformance and time requirement analysis of top hat transform based small target detection algorithms

Date

2015-04-24

Author

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

113
views

0
downloads

Top-Hat transform is well known background suppression method used in small target detection. In this paper, we investigate various different Top-Hat transformation based small target detection approaches. All of the methods are implemented with their best parameter settings and applied to the same test image. The comparison among them is done in terms of three issues: 1. the detection performance (precision and false alarm rate), 2. the time requirement of the method and its usability for real time applications, 3. the number of parameters, which need user interaction. Results show that all of the algorithms require a prior knowledge of target size, which is either used as the structuring element size or as the threshold for post-processing. Algorithms, which use automatic approaches to select its parameters, are not generic to be applied to various images. But algorithms, which use adaptive methods for deciding on the threshold value, perform better than the others.

Subject Keywords

Small target detection, Real-time methods, Mathematical morphology, Wavelet transform, Infrared missile seeker, Infrared imagery, Background suppression, Top-Hat transform

URI

https://hdl.handle.net/11511/38384

DOI

https://doi.org/10.1117/12.2176325

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Robust Automatic Target Recognition in FLIR imagery Soyman, Yusuf (2012-04-24) In this paper, a robust automatic target recognition algorithm in FLIR imagery is proposed. Target is first segmented out from the background using wavelet transform. Segmentation process is accomplished by parametric Gabor wavelet transformation. Invariant features that belong to the target, which is segmented out from the background, are then extracted via moments. Higher-order moments, while providing better quality for identifying the image, are more sensitive to noise. A trade-off study is then perform...
Utilization of dense depth information for monoview object detection and instance segmentation Çakırgöz, Çağlayan Can; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2022-5-10) Object detection aims for detecting objects of certain classes in an image by bounding them in rectangular boxes whereas instance segmentation tries to detect objects in pixel level. Deep learning techniques, which have shown great improvements over the last decade, are utilized in these topics as well, and a significant success is achieved against the traditional methods. Similar improvements can be observed in dense depth estimation which deals with deducing dense information of a scene from a single imag...
Evaluation of potential novel variations and their interactions related to bipolar disorders: Analysis of genome-wide association study data AÇIKEL, Cengizhan; Aydın Son, Yeşim; ÇELİK, Cemil; GÜL, Husamettin (2016-11-24) Background: Multifactor dimensionality reduction (MDR) is a nonparametric approach that can be used to detect relevant interactions between single-nucleotide polymorphisms (SNPs). The aim of this study was to build the best genomic model based on SNP associations and to identify candidate polymorphisms that are the underlying molecular basis of the bipolar disorders. Methods: This study was performed on Whole-Genome Association Study of Bipolar Disorder (dbGaP [database of Genotypes and Phenotypes] study ac...
Posterior Cram'er-Rao Lower Bounds for Extended Target Tracking with Random Matrices Sarıtaş, Elif; Orguner, Umut (2016-07-08) This paper presents posterior Cram'er-Rao lower bounds (PCRLB) for extended target tracking (ETT) when the extent states of the targets are represented with random matrices. PCRLB recursions are derived for kinematic and extent states taking complicated expectations involving Wishart and inverse Wishart distributions. For some analytically intractable expectations, Monte Carlo integration is used. The bounds for the semi-major and minor axes of the extent ellipsoid are obtained as well as those for the exte...
Correlation tracking based on wavelet domain information Ipek, HL; Yilmaz, I; Yardimci, YC; Cetin, AE (2003-08-07) Tracking moving objects in video can be carried out by correlating a template containing object pixels with pixels of the current frame. This approach may produce erroneous results under noise. We determine a set of significant pixels on the object by analyzing the wavelet transform of the template and correlate only these pixels with the current frame to determine the next position of the object. These significant pixels are easily trackable features of the image and increase the performance of the tracker.

Citation Formats

İ. Ulusoy, “PErformance and time requirement analysis of top hat transform based small target detection algorithms,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38384.