An efficient algorithm to decompose a compound rectilinear shape into simple rectilinear shapes

Imran Sharif, Debasis Chaudhuri, Naveen Kumar Kushwaha, Ashok K Samal, Brij Mohan Singh

Research output: Contribution to journalArticle

Abstract

Detection of a compound object is a critical problem in target recognition. For example, buildings form an important class of shapes whose recognition is important in many remote sensing based applications. Due to the coarse resolution of imaging sensors, adjacent buildings in the scenes appear as a single compound shape object. These compound objects can be represented as the union of a set of disjoint rectilinear shaped objects. Separating the individual buildings from the resulting compound objects in a segmented image is often difficult but important nevertheless. In this paper we propose a new and efficient technique to decompose a compound shape into a set of simple rectilinear shapes. First, the true interior and exterior corner points of the compound object are extracted. A modified corner detector based on polygonal approximation is proposed to accurately determine the boundaries of compound shapes. The compound shape is then split at the interior corner points to minimize the difference between the perimeter of the compound object and the sum of the perimeters of the decomposed objects. We have systematically compared the results our algorithm with those of existing approaches and the results show that the proposed algorithm is more accurate than the algorithms in the literature in terms of accuracy of perimeter estimation and computational cost.

Original languageEnglish (US)
Pages (from-to)150-161
Number of pages12
JournalTurkish Journal of Electrical Engineering and Computer Sciences
Volume26
Issue number1
DOIs
StatePublished - Jan 1 2018

Fingerprint

Remote sensing
Detectors
Imaging techniques
Sensors
Costs

Keywords

  • Building extraction
  • Compound object
  • Corner point detection
  • Feature extraction
  • Pattern recognition
  • Shape analysis

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

Cite this

An efficient algorithm to decompose a compound rectilinear shape into simple rectilinear shapes. / Sharif, Imran; Chaudhuri, Debasis; Kushwaha, Naveen Kumar; Samal, Ashok K; Singh, Brij Mohan.

In: Turkish Journal of Electrical Engineering and Computer Sciences, Vol. 26, No. 1, 01.01.2018, p. 150-161.

Research output: Contribution to journalArticle

Sharif, Imran ; Chaudhuri, Debasis ; Kushwaha, Naveen Kumar ; Samal, Ashok K ; Singh, Brij Mohan. / An efficient algorithm to decompose a compound rectilinear shape into simple rectilinear shapes. In: Turkish Journal of Electrical Engineering and Computer Sciences. 2018 ; Vol. 26, No. 1. pp. 150-161.
@article{407ff1cdca3441fa97896c565c68c97e,
title = "An efficient algorithm to decompose a compound rectilinear shape into simple rectilinear shapes",
abstract = "Detection of a compound object is a critical problem in target recognition. For example, buildings form an important class of shapes whose recognition is important in many remote sensing based applications. Due to the coarse resolution of imaging sensors, adjacent buildings in the scenes appear as a single compound shape object. These compound objects can be represented as the union of a set of disjoint rectilinear shaped objects. Separating the individual buildings from the resulting compound objects in a segmented image is often difficult but important nevertheless. In this paper we propose a new and efficient technique to decompose a compound shape into a set of simple rectilinear shapes. First, the true interior and exterior corner points of the compound object are extracted. A modified corner detector based on polygonal approximation is proposed to accurately determine the boundaries of compound shapes. The compound shape is then split at the interior corner points to minimize the difference between the perimeter of the compound object and the sum of the perimeters of the decomposed objects. We have systematically compared the results our algorithm with those of existing approaches and the results show that the proposed algorithm is more accurate than the algorithms in the literature in terms of accuracy of perimeter estimation and computational cost.",
keywords = "Building extraction, Compound object, Corner point detection, Feature extraction, Pattern recognition, Shape analysis",
author = "Imran Sharif and Debasis Chaudhuri and Kushwaha, {Naveen Kumar} and Samal, {Ashok K} and Singh, {Brij Mohan}",
year = "2018",
month = "1",
day = "1",
doi = "10.3906/elk-1608-50",
language = "English (US)",
volume = "26",
pages = "150--161",
journal = "Turkish Journal of Electrical Engineering and Computer Sciences",
issn = "1300-0632",
publisher = "Turkiye Klinikleri",
number = "1",

}

TY - JOUR

T1 - An efficient algorithm to decompose a compound rectilinear shape into simple rectilinear shapes

AU - Sharif, Imran

AU - Chaudhuri, Debasis

AU - Kushwaha, Naveen Kumar

AU - Samal, Ashok K

AU - Singh, Brij Mohan

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Detection of a compound object is a critical problem in target recognition. For example, buildings form an important class of shapes whose recognition is important in many remote sensing based applications. Due to the coarse resolution of imaging sensors, adjacent buildings in the scenes appear as a single compound shape object. These compound objects can be represented as the union of a set of disjoint rectilinear shaped objects. Separating the individual buildings from the resulting compound objects in a segmented image is often difficult but important nevertheless. In this paper we propose a new and efficient technique to decompose a compound shape into a set of simple rectilinear shapes. First, the true interior and exterior corner points of the compound object are extracted. A modified corner detector based on polygonal approximation is proposed to accurately determine the boundaries of compound shapes. The compound shape is then split at the interior corner points to minimize the difference between the perimeter of the compound object and the sum of the perimeters of the decomposed objects. We have systematically compared the results our algorithm with those of existing approaches and the results show that the proposed algorithm is more accurate than the algorithms in the literature in terms of accuracy of perimeter estimation and computational cost.

AB - Detection of a compound object is a critical problem in target recognition. For example, buildings form an important class of shapes whose recognition is important in many remote sensing based applications. Due to the coarse resolution of imaging sensors, adjacent buildings in the scenes appear as a single compound shape object. These compound objects can be represented as the union of a set of disjoint rectilinear shaped objects. Separating the individual buildings from the resulting compound objects in a segmented image is often difficult but important nevertheless. In this paper we propose a new and efficient technique to decompose a compound shape into a set of simple rectilinear shapes. First, the true interior and exterior corner points of the compound object are extracted. A modified corner detector based on polygonal approximation is proposed to accurately determine the boundaries of compound shapes. The compound shape is then split at the interior corner points to minimize the difference between the perimeter of the compound object and the sum of the perimeters of the decomposed objects. We have systematically compared the results our algorithm with those of existing approaches and the results show that the proposed algorithm is more accurate than the algorithms in the literature in terms of accuracy of perimeter estimation and computational cost.

KW - Building extraction

KW - Compound object

KW - Corner point detection

KW - Feature extraction

KW - Pattern recognition

KW - Shape analysis

UR - http://www.scopus.com/inward/record.url?scp=85041323596&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85041323596&partnerID=8YFLogxK

U2 - 10.3906/elk-1608-50

DO - 10.3906/elk-1608-50

M3 - Article

AN - SCOPUS:85041323596

VL - 26

SP - 150

EP - 161

JO - Turkish Journal of Electrical Engineering and Computer Sciences

JF - Turkish Journal of Electrical Engineering and Computer Sciences

SN - 1300-0632

IS - 1

ER -