Remote Sens. 2009, 1(4), 731-757; doi:10.3390/rs1040731
Article

Automatic Vegetation Identification and Building Detection from a Single Nadir Aerial Image

Nicholas Shorter* email and Takis Kasparisemail
School of Electrical Engineering and Computer Science (EECS), University of Central Florida (UCF), 4000 Central Florida Blvd., Orlando, FL 32816-2362, USA
* Author to whom correspondence should be addressed.
Received: 18 September 2009; in revised form: 30 September 2009 / Accepted: 13 October 2009 / Published: 16 October 2009
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Abstract: A novel, automatic tertiary classifier is proposed for identifying vegetation, building and non-building objects from a single nadir aerial image. The method is unsupervised, that is, no parameter adjustment is done during the algorithm’s execution. The only assumption the algorithm makes about the building structures is that they have convex rooftop sections. Results are provided for two different actual data sets.
Keywords: vegetation identification; building detection; color invariants; nadir aerial image

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Cite This Article

MDPI and ACS Style

Shorter, N.; Kasparis, T. Automatic Vegetation Identification and Building Detection from a Single Nadir Aerial Image. Remote Sens. 2009, 1, 731-757.

AMA Style

Shorter N, Kasparis T. Automatic Vegetation Identification and Building Detection from a Single Nadir Aerial Image. Remote Sensing. 2009; 1(4):731-757.

Chicago/Turabian Style

Shorter, Nicholas; Kasparis, Takis. 2009. "Automatic Vegetation Identification and Building Detection from a Single Nadir Aerial Image." Remote Sens. 1, no. 4: 731-757.

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