SPIE10 Abstract

SPIE10 Paper

SPIE10 Presentation

Derek

Well I thought I would let everyone know that I passed my Ph.D. Qualifier today. It was a little stressful and glad that step 1 of 3 is done. I have also enjoyed being in Colorado and catching up with everyone and seeing our great friends here. I am truly thankful to the Andrew’s for letting me crash in their basement during the week and for the Miller’s for letting me stay with the in Denver. It has been weird to think that we have been gone from Colorado for 6 Months. I have also posted my slides below from my presentation for anybody that would like to check them out.

PhD Qualifier Slides

Derek

I just presented two paper at the IEEE/MTS Oceans Conference Biloxi, MS. I have attached the slides and paper below for those who might want to read it.

The first paper was entitled “Multi-Platform Target Detection using Multi-Channel Coherence Analysis and Robustness to the Effects of Disparity”

Abstract

The use of multiple disparate platforms in many remote sensing and surveillance applications allows one to exploit the coherent information shared among all sensory systems thereby potentially reducing the risk of making single-sensory biased detection and classification decisions.  This paper introduces a target detection method based upon multi-channel coherence analysis (MCA) framework which optimally decomposes the multi-channel data to analyze their linear dependence or coherence.  This decomposition then allows one to extract MCA features that can be used to implement a coherence-based detector.  This detector is applied to a data set of simulated disparate sonar imagery provided by the Naval Surface Warfare Center (NSWC) – Panama City.  This database contains images of both targets and non-targets with various variabilities with respect to resolution, signal-to-noise ratio (SNR), target and non-target types, etc.  Sensitivity analyses are then carried out in order to gauge the performance under such variablities that may be encountered in disparate multi-platform detection problems.  Performance of the detection method will be given in terms of probability of detection (Pd), probability of false alarm (Pfa), and the receiver operating characteristic (ROC) curves.

Oceans09 Multiplatform Paper

Oceans09 Multiplatform Slides

The first paper was entitled “An Underwater Target Detection System for Electro-Optical Imagery Data”

Abstract

The problem of detecting underwater targets from Electro-optical (EO) images is considered in this paper. A block-based log-likelihood ratio test has been developed for detection and segmentation of underwater mine-like objects in the EO images captured with a CCD-based image sensor. The main focus of this research is to develop a robust detection algorithm that can be used to detect low contrast and partial underwater objects from the EO imagery with low false alarm rate. The detection method involves identifying frames of interest (FOI) containing the potential targets. Once the FOI have been identified, regions of interest (ROI) within the FOI are segmented from the background. Performance of the detection method is tested in terms of probability of detection, false alarm rate, and receiver operating characteristic (ROC) curves for FOI in the selected data runs. The algorithm shows promising results in target detection and generation of good silhouettes for subsequent classification.

Oceans09 EO Paper

Oceans09 EO Slides

Derek

Abstract

This paper introduces a new target detection method for multiple disparate sonar platforms.  The detection method is based upon multi-channel coherence analysis (MCA) framework which allows one to optimally decompose the multi-channel data to analyze their linear dependence or coherence.  This decomposition then allows one to extract MCA features which can be used to discriminate between two hypotheses, one corresponding to the presence of a target and one without, through the use of the log-likelihood ratio.  Test results of the proposed detection system were applied to a data set of underwater side-scan sonar imagery provided by the Naval Surface Warfare Center (NSWC), Panama City.  This database contains data from 4 disparate sonar systems, namely one high frequency (HF) sonar and three broadband (BB) sonars coregistered over the same area on the sea floor.  Test results illustrate the effectiveness of the proposed multi-platform detection system in terms of probability of detection, false alarm rate, and receiver operating characteristic (ROC) curves.

SMC09 Paper

SMC09 Slides

JDT M.S. Thesis

MS Defense Presentation

Derek

MS Defense Presentation

Derek

Sea Technology 08 Original

Sea Technology 08 Final PDF

Derek

http://www.sea-technology.com/

It was neat to see this on on the website

COHERENCE-BASED TARGET DETECTION AND
CLASSIFICATION FOR SIDE SCAN SONAR IMAGERY
J. Derek Tucker and Mahmood R. Azimi-Sadjadi (Colorado State University) explore the use of canonical correlation analysis for sonar target detection and classification.

I hope everyone is well and Merry Christmas!

Derek

Oceans 2008 Abstract

Oceans 2008 Paper

Oceans 2008 Slides

Derek

I actually am attending and will be at the entire week a conference for my research, SPIE Defense and Security Symposium in Orlando Florida. The conference has been a very interesting and good way to make contacts and get feedback on my research. If you click on the links below you will can take a look at the paper I wrote for the conference as well as my slides of the presentation I gave. The work was on the multiplatform underwater mine detection using canonical correlations.

Other than that we have just been keeping busy with work, school, and skiing . I also got a new calling at church which is exciting. I am the new Priest Quorom advisor and Venture Crew Advisor. I am excited as I get to spend time with the boys outdoors doing High Adventure which we have already have had one snowshoe backpacking trip with another in the works. Well I hope all is well and talk to you soon.

Derek and Nichole

SPIE DSS 08 Abstract

SPIE DSS 08 Paper

SPIE DSS 08 Slides