Implementation of a Segmentation Method for Agricultural Fields in Aerial Sequences of Images Based on CSAR Model

H. Chen; Z. Houkes

doi:10.1117/12.324129

Implementation of a Segmentation Method for Agricultural Fields in Aerial Sequences of Images Based on CSAR Model

H. Chen, Z. Houkes

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

In this paper, a segmentation method for agricultural fields in aerial sequences of images based on the Circular Symmetri Auto-Regressive (CSAR) model is presented. The image sequences assumed to be acquired by a video camera (RGB-CCD system) from an aeroplane, which moves linearly over the scene. The objects in the scenes being considered in this paper, are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes sugar beet, wheat, etc. In order to recognize and classify these fields from aerial sequence of images, a reliable segmentatio is required. Here texture features are used for segmentation. The implementation of segmentation for agricultural fields in aerial sequences of images is based on CSAR model in texture analysis. By comparing the estimated parameters of CSAR model from different area in an image, the characteristics and the class of a texture may be determined. The paper describes the segmentation method and its evaluation through experiments. Based on segmentation results, classification for surface texture of vegetation from aerial sequences of images is realized.

Original language	English
Title of host publication	Electronic imaging
Subtitle of host publication	processing, printing, and publishing in color : 18-20 May 1998, Zurich, Switzerland
Editors	Jan Bareš
Place of Publication	Bellingham, WA
Publisher	SPIE
Pages	368-376
Number of pages	9
ISBN (Print)	9780819428615
DOIs	https://doi.org/10.1117/12.324129
Publication status	Published - 1998
Event	SYBEN-Broadband European Networks and Electronic Image Capture and Publishing 1998 - Zurich, Switzerland Duration: 18 May 1998 → 22 May 1998

Publication series

Name	Proceedings of SPIE
Publisher	SPIE
Volume	3409
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	SYBEN-Broadband European Networks and Electronic Image Capture and Publishing 1998
Country	Switzerland
City	Zurich
Period	18/05/98 → 22/05/98

Keywords

METIS-112569

Access to Document

10.1117/12.324129

Fingerprint Dive into the research topics of 'Implementation of a Segmentation Method for Agricultural Fields in Aerial Sequences of Images Based on CSAR Model'. Together they form a unique fingerprint.

Cite this

Chen, H., & Houkes, Z. (1998). Implementation of a Segmentation Method for Agricultural Fields in Aerial Sequences of Images Based on CSAR Model. In J. Bareš (Ed.), Electronic imaging: processing, printing, and publishing in color : 18-20 May 1998, Zurich, Switzerland (pp. 368-376). (Proceedings of SPIE; Vol. 3409). Bellingham, WA: SPIE. https://doi.org/10.1117/12.324129

@inbook{2b2133d344324a7eb4bdf671c41abee0,

title = "Implementation of a Segmentation Method for Agricultural Fields in Aerial Sequences of Images Based on CSAR Model",

abstract = "In this paper, a segmentation method for agricultural fields in aerial sequences of images based on the Circular Symmetri Auto-Regressive (CSAR) model is presented. The image sequences assumed to be acquired by a video camera (RGB-CCD system) from an aeroplane, which moves linearly over the scene. The objects in the scenes being considered in this paper, are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes sugar beet, wheat, etc. In order to recognize and classify these fields from aerial sequence of images, a reliable segmentatio is required. Here texture features are used for segmentation. The implementation of segmentation for agricultural fields in aerial sequences of images is based on CSAR model in texture analysis. By comparing the estimated parameters of CSAR model from different area in an image, the characteristics and the class of a texture may be determined. The paper describes the segmentation method and its evaluation through experiments. Based on segmentation results, classification for surface texture of vegetation from aerial sequences of images is realized.",

keywords = "METIS-112569",

author = "H. Chen and Z. Houkes",

year = "1998",

doi = "10.1117/12.324129",

language = "English",

isbn = "9780819428615",

series = "Proceedings of SPIE",

publisher = "SPIE",

pages = "368--376",

editor = "Jan Bareš",

booktitle = "Electronic imaging",

address = "United States",

}

Chen, H & Houkes, Z 1998, Implementation of a Segmentation Method for Agricultural Fields in Aerial Sequences of Images Based on CSAR Model. in J Bareš (ed.), Electronic imaging: processing, printing, and publishing in color : 18-20 May 1998, Zurich, Switzerland. Proceedings of SPIE, vol. 3409, SPIE, Bellingham, WA, pp. 368-376, SYBEN-Broadband European Networks and Electronic Image Capture and Publishing 1998, Zurich, Switzerland, 18/05/98. https://doi.org/10.1117/12.324129

Implementation of a Segmentation Method for Agricultural Fields in Aerial Sequences of Images Based on CSAR Model. / Chen, H.; Houkes, Z.

Electronic imaging: processing, printing, and publishing in color : 18-20 May 1998, Zurich, Switzerland. ed. / Jan Bareš. Bellingham, WA : SPIE, 1998. p. 368-376 (Proceedings of SPIE; Vol. 3409).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

TY - CHAP

T1 - Implementation of a Segmentation Method for Agricultural Fields in Aerial Sequences of Images Based on CSAR Model

AU - Chen, H.

AU - Houkes, Z.

PY - 1998

Y1 - 1998

N2 - In this paper, a segmentation method for agricultural fields in aerial sequences of images based on the Circular Symmetri Auto-Regressive (CSAR) model is presented. The image sequences assumed to be acquired by a video camera (RGB-CCD system) from an aeroplane, which moves linearly over the scene. The objects in the scenes being considered in this paper, are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes sugar beet, wheat, etc. In order to recognize and classify these fields from aerial sequence of images, a reliable segmentatio is required. Here texture features are used for segmentation. The implementation of segmentation for agricultural fields in aerial sequences of images is based on CSAR model in texture analysis. By comparing the estimated parameters of CSAR model from different area in an image, the characteristics and the class of a texture may be determined. The paper describes the segmentation method and its evaluation through experiments. Based on segmentation results, classification for surface texture of vegetation from aerial sequences of images is realized.

AB - In this paper, a segmentation method for agricultural fields in aerial sequences of images based on the Circular Symmetri Auto-Regressive (CSAR) model is presented. The image sequences assumed to be acquired by a video camera (RGB-CCD system) from an aeroplane, which moves linearly over the scene. The objects in the scenes being considered in this paper, are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes sugar beet, wheat, etc. In order to recognize and classify these fields from aerial sequence of images, a reliable segmentatio is required. Here texture features are used for segmentation. The implementation of segmentation for agricultural fields in aerial sequences of images is based on CSAR model in texture analysis. By comparing the estimated parameters of CSAR model from different area in an image, the characteristics and the class of a texture may be determined. The paper describes the segmentation method and its evaluation through experiments. Based on segmentation results, classification for surface texture of vegetation from aerial sequences of images is realized.

KW - METIS-112569

U2 - 10.1117/12.324129

DO - 10.1117/12.324129

M3 - Chapter

SN - 9780819428615

T3 - Proceedings of SPIE

SP - 368

EP - 376

BT - Electronic imaging

A2 - Bareš, Jan

PB - SPIE

CY - Bellingham, WA

ER -