"Target segmentation and detection problem is one of the preliminary approaches in analyzing an image. Many edge, region and texture based techniques have been proposed in literature. These techniques often have limitations based on types of image data, kind of segmentation of interest and the problem domain. Mine detection problem dealt with for this thesis has mine target images which have a center target consisting of false alarm or mine patch which has to be detected and features evaluated to evaluate various parameter performances. Thus, segmenting the mine patch becomes the first step of analyzing these images. This thesis is divided into two parts. First part deals with segmenting the single and multi-band mine linages for target detection. An immersion-based watershed approach is adopted with median filtering to obtain a continuous image and thus a better segmentation. The over segmentation caused by watershed algorithm is addressed by using the region dissimilarity criterion for region merging. The second part of tills thesis consists of discussion about various spectral features devised to identify the "mineness" of the target detected thus aiding in determining if the target is a mine or a false alarm. False alarm study is one of the major parts in mine detection as there are many false alarm signatures similar to mines. This is discussed in more detail and segmentation results and Receiver Operating Curves (ROCs) for false alarm study is presented wherever relevant"--Abstract, page iii.
Agarwal, Sanjeev, 1971-
Moss, Randy Hays, 1953-
Electrical and Computer Engineering
M.S. in Computer Engineering
Night Vision Laboratory. Countermine Division
Missouri University of Science and Technology
ix, 46 pages
© 2010 Deepika Kamakshi Timmavajjula, All rights reserved.
Thesis - Restricted Access
Image processing -- Computer programs
Mines (Military explosives) -- Detection
Receiver operating characteristic curves -- Computer programs
Image processing -- Mathematics
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Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.http://merlin.lib.umsystem.edu:80/record=b10251198~S5
Timmavajjula, Deepika Kamakshi, "Target detection and feature evaluation of airborne mine target images" (2010). Masters Theses. 4522.
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