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Investigation of computational probl...

Cole, Kevin.

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Investigation of computational problem area detection on earthen spillways across varying image resolutions.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Investigation of computational problem area detection on earthen spillways across varying image resolutions./
作者:	Cole, Kevin.
面頁冊數:	69 p.
附註:	Source: Masters Abstracts International, Volume: 49-01, page: 0485.
Contained By:	Masters Abstracts International49-01.
標題:	Agriculture, Soil Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1480973
ISBN:	9781124210582

Investigation of computational problem area detection on earthen spillways across varying image resolutions.
Cole, Kevin.

Investigation of computational problem area detection on earthen spillways across varying image resolutions. - 69 p.

Source: Masters Abstracts International, Volume: 49-01, page: 0485.

Thesis (M.S.)--Oklahoma State University, 2010.

This thesis work investigates the ability of segmentation algorithms to segment vegetal problem areas in aerial images of earthen spillways. Four different segmentation algorithms were applied to aerial images of spillways that were resized to 8 different resolutions. Segmentation results from each algorithm and spillway resolution were analyzed on the basis of the percentage of pixels segmented for each problem area using a manually segmented image as a ground truth for comparison.

ISBN: 9781124210582Subjects--Topical Terms:

1017824
Agriculture, Soil Science.

Investigation of computational problem area detection on earthen spillways across varying image resolutions.
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520 $a This thesis work investigates the ability of segmentation algorithms to segment vegetal problem areas in aerial images of earthen spillways. Four different segmentation algorithms were applied to aerial images of spillways that were resized to 8 different resolutions. Segmentation results from each algorithm and spillway resolution were analyzed on the basis of the percentage of pixels segmented for each problem area using a manually segmented image as a ground truth for comparison.
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