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Saliency-Based CBIR System for Exploring Lunar Surface Imagery

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Conference

2014 ASEE Annual Conference & Exposition

Location

Indianapolis, Indiana

Publication Date

June 15, 2014

Start Date

June 15, 2014

End Date

June 18, 2014

ISSN

2153-5965

Conference Session

New Trends in Computing and Information Technology Education

Tagged Division

Computing & Information Technology

Page Count

18

Page Numbers

24.1065.1 - 24.1065.18

Permanent URL

https://peer.asee.org/22998

Download Count

38

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Paper Authors

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Kien A. Hua University of Central Florida

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Kien A. Hua received the BS degree in computer science and the MS and PhD degrees in electrical engineering, all from the University of Illinois at Urbana-Champaign. He is currently a professor in the School of Electrical Engineering and Computer Science, and is the Director of the Data Systems Lab at the University of Central Florida. His research interests include image and video retrieval, medical imaging, network and wireless communications, sensor computing, location-based services, and intelligent transportation systems. Dr. Hua has published widely, including several papers recognized as best/top papers at various international conferences. He has served as a conference chair, vice-chair, associate chair, demo chair, and program committee member for numerous conferences, and on the editorial board of the IEEE Transactions on Knowledge and Data Engineering, Journal of Multimedia Tools and Applications, and the International Journal of Advanced Information Technology. Dr. Hua is a Fellow of IEEE.

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Gholam Ali Shaykhian NASA

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Ali Shaykhian (Ali.Shaykhian@nasa.gov) is an engineer with National Aeronautics and Space Administration (NASA), Kennedy Space Center (KSC), Information Technology (IT) Directorate. Ali has earned his Ph.D. in Operations Research from Florida Institute of Technology (FIT). He has received a Master of Science (M.S.) degree in Computer Systems from University of Central Florida and a second M.S. degree in Operations Research from the same university. His research interests include knowledge management, data mining, object-oriented methodologies, design patterns, software safety, genetic and optimization algorithms and data mining. Dr. Shaykhian is a professional member of the American Society for Engineering Education (ASEE), serving as the past Program Chair for the Minorities in Engineering Division.

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Robert J Beil NASA Engineering and Safety Center

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Mr Beil currently serves as a Systems Engineer for the NASA Engineering & Safety Centers (NESC) Systems Engineering Office (SEO). Mr. Beil was the requirements manager and systems engineer for the developmental, full scale Max Launch Abort System project. He leads an NASA, agency level data mining and trending working group. He worked for many years as the Orbiter Main Propulsion System (MPS) lead engineer at Kennedy Space Center. He earned a Bachelor of Science in Mechanical Engineering from Old Dominion University (Norfolk, VA) and a Master of Science in Industrial Engineering from the University of Central Florida.

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KUTALMIS AKPINAR School of Electrical Engineering and Computer Science, University of Central Florida

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Kutalmis Akpinar is a Ph.D. student at the University of Central Florida, Orlando. He received his B.Sc. degree in Electrical and Electronics Engineering from Bilkent University, Turkey in 2009 and his M.S. in Electrical and Electronics Engineering from the Middle East Technical University, Turkey in 2012. From 2009 to 2012, he was also a researcher in the Informatics and Information Security Research Center, Turkey. His past experience includes human activity recognition features and surveillance systems. He is currently a member of the Database System Group (DSG) at UCF and is working on new techniques for image retrieval in image database systems.

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Kyle A. Martin University of Central Florida

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Abstract

Saliency-Based CBIR System for Exploring Lunar Surface ImageryRecent NASA missions like the Lunar Reconnaissance Orbiter (LRO) have produced vastarchives of surface imagery which must be analyzed to locate landmarks with distinctive visualfeatures, like craters, which provide important information about geologic history and potentialmineral resources. Content Based Image Retrieval allows large archives of images to beefficiently queried based on visual content by indexing multidimensional feature vectorsextracted from the images. Unlike images of particular objects or scenes traditionally retrievedusing CBIR, surface images are not focused on any particular landmark so they must be pre-processed to identify Regions of Interest (ROI) to be indexed for retrieval. Previous workidentified ROIs using manual annotation and expensive detection algorithms for specific types oflandmarks, such as Crater Detection Algorithms (CDA). In contrast, this work utilizes a general-purpose saliency-based landmark detection algorithm for identifying ROIs which are thenindexed for retrieval using feature vectors extracted from the ROI images. We evaluate theretrieval performance of several feature vectors and assess the saliency-based landmark detectionperformance in comparison to a comprehensive crater database created using manual annotationand a CDA. Experimental results demonstrate the advantages of the general-purpose saliency-based CBIR system for exploring lunar surface imagery.

Hua, K. A., & Shaykhian, G. A., & Beil, R. J., & AKPINAR, K., & Martin, K. A. (2014, June), Saliency-Based CBIR System for Exploring Lunar Surface Imagery Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. https://peer.asee.org/22998

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