Object-based classification and building extraction by integrating airborne LiDAR data and aerial image

Yongmin Kim; Youkyung Han; Junho Yeom; Dongyeob Han; Yongil Kim

doi:10.1109/IGARSS.2012.6352673

Object-based classification and building extraction by integrating airborne LiDAR data and aerial image

Yongmin Kim, Youkyung Han, Junho Yeom, Dongyeob Han, Yongil Kim

Dept. of Civil Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

It is generally difficult to classify an object type having different colors into the same class using only optical data such as a satellite or aerial image. This paper proposes a method that solves this problem by combining LiDAR data and an aerial image. The method extracts building pixels from LiDAR data and then identifies building objects on the aerial image by overlaying the LiDAR result to a segmented aerial image through the definite rule. This process plays a role in transforming building objects of LiDAR data to ones of the aerial image.

Original language	English
Pages	6200-6202
Number of pages	3
DOIs	https://doi.org/10.1109/IGARSS.2012.6352673
State	Published - 2012
Event	2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany Duration: 22 Jul 2012 → 27 Jul 2012

Conference

Conference	2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
Country/Territory	Germany
City	Munich
Period	22/07/12 → 27/07/12

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10.1109/IGARSS.2012.6352673

Cite this

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abstract = "It is generally difficult to classify an object type having different colors into the same class using only optical data such as a satellite or aerial image. This paper proposes a method that solves this problem by combining LiDAR data and an aerial image. The method extracts building pixels from LiDAR data and then identifies building objects on the aerial image by overlaying the LiDAR result to a segmented aerial image through the definite rule. This process plays a role in transforming building objects of LiDAR data to ones of the aerial image.",

author = "Yongmin Kim and Youkyung Han and Junho Yeom and Dongyeob Han and Yongil Kim",

year = "2012",

doi = "10.1109/IGARSS.2012.6352673",

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AU - Kim, Yongmin

AU - Han, Youkyung

AU - Yeom, Junho

AU - Han, Dongyeob

AU - Kim, Yongil

PY - 2012

Y1 - 2012

N2 - It is generally difficult to classify an object type having different colors into the same class using only optical data such as a satellite or aerial image. This paper proposes a method that solves this problem by combining LiDAR data and an aerial image. The method extracts building pixels from LiDAR data and then identifies building objects on the aerial image by overlaying the LiDAR result to a segmented aerial image through the definite rule. This process plays a role in transforming building objects of LiDAR data to ones of the aerial image.

AB - It is generally difficult to classify an object type having different colors into the same class using only optical data such as a satellite or aerial image. This paper proposes a method that solves this problem by combining LiDAR data and an aerial image. The method extracts building pixels from LiDAR data and then identifies building objects on the aerial image by overlaying the LiDAR result to a segmented aerial image through the definite rule. This process plays a role in transforming building objects of LiDAR data to ones of the aerial image.

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T2 - 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012

Y2 - 22 July 2012 through 27 July 2012

ER -

Object-based classification and building extraction by integrating airborne LiDAR data and aerial image

Abstract

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