Detection and recognition method for irregular craters on planetary surface

Zheng Shi Yu; Sheng Ying Zhu; Dong Mei Ma; Ping Yuan Cui

doi:10.3873/j.issn.1000-1328.2013.03.004

Detection and recognition method for irregular craters on planetary surface

Zheng Shi Yu^*, Sheng Ying Zhu, Dong Mei Ma, Ping Yuan Cui

^*Corresponding author for this work

School of Aerospace Engineering

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

The paper focuses on the feature detection and recognition on planetary surface in the deep space exploration mission. A novel detection and recognition method for irregular craters, especially overlapped and incomplete craters on planetary surface is proposed. First, extraction of candidate crater edge is performed by using the Contextual-based Hopfield neural network. Furthermore, pseudo-edges which do not satisfy the constraints are removed by analyzing multi constraints for real crater edges. Finally, real edges containing the feature of the crater are detected by using the least median square ellipse fitting method combined with a robust least square method. Meanwhile the physical parameters are determined. Mathematical simulations demonstrate the performance of the proposed method for detection and recognition of irregular craters in complex background.

Original language	English
Pages (from-to)	320-326
Number of pages	7
Journal	Yuhang Xuebao/Journal of Astronautics
Volume	34
Issue number	3
DOIs	https://doi.org/10.3873/j.issn.1000-1328.2013.03.004
Publication status	Published - Mar 2013

Keywords

Contextual-based Hopfield neural network (CHNN)
Crater detection
Least median square ellipse
Multi constraints
Robust least square method

Access to Document

10.3873/j.issn.1000-1328.2013.03.004

Cite this

@article{41787fdca74f4aa9b698dc1c958ff8e4,

title = "Detection and recognition method for irregular craters on planetary surface",

abstract = "The paper focuses on the feature detection and recognition on planetary surface in the deep space exploration mission. A novel detection and recognition method for irregular craters, especially overlapped and incomplete craters on planetary surface is proposed. First, extraction of candidate crater edge is performed by using the Contextual-based Hopfield neural network. Furthermore, pseudo-edges which do not satisfy the constraints are removed by analyzing multi constraints for real crater edges. Finally, real edges containing the feature of the crater are detected by using the least median square ellipse fitting method combined with a robust least square method. Meanwhile the physical parameters are determined. Mathematical simulations demonstrate the performance of the proposed method for detection and recognition of irregular craters in complex background.",

keywords = "Contextual-based Hopfield neural network (CHNN), Crater detection, Least median square ellipse, Multi constraints, Robust least square method",

author = "Yu, {Zheng Shi} and Zhu, {Sheng Ying} and Ma, {Dong Mei} and Cui, {Ping Yuan}",

year = "2013",

month = mar,

doi = "10.3873/j.issn.1000-1328.2013.03.004",

language = "English",

volume = "34",

pages = "320--326",

journal = "Yuhang Xuebao/Journal of Astronautics",

issn = "1000-1328",

publisher = "Chinese Society of Astronautics",

number = "3",

}

TY - JOUR

T1 - Detection and recognition method for irregular craters on planetary surface

AU - Yu, Zheng Shi

AU - Zhu, Sheng Ying

AU - Ma, Dong Mei

AU - Cui, Ping Yuan

PY - 2013/3

Y1 - 2013/3

N2 - The paper focuses on the feature detection and recognition on planetary surface in the deep space exploration mission. A novel detection and recognition method for irregular craters, especially overlapped and incomplete craters on planetary surface is proposed. First, extraction of candidate crater edge is performed by using the Contextual-based Hopfield neural network. Furthermore, pseudo-edges which do not satisfy the constraints are removed by analyzing multi constraints for real crater edges. Finally, real edges containing the feature of the crater are detected by using the least median square ellipse fitting method combined with a robust least square method. Meanwhile the physical parameters are determined. Mathematical simulations demonstrate the performance of the proposed method for detection and recognition of irregular craters in complex background.

AB - The paper focuses on the feature detection and recognition on planetary surface in the deep space exploration mission. A novel detection and recognition method for irregular craters, especially overlapped and incomplete craters on planetary surface is proposed. First, extraction of candidate crater edge is performed by using the Contextual-based Hopfield neural network. Furthermore, pseudo-edges which do not satisfy the constraints are removed by analyzing multi constraints for real crater edges. Finally, real edges containing the feature of the crater are detected by using the least median square ellipse fitting method combined with a robust least square method. Meanwhile the physical parameters are determined. Mathematical simulations demonstrate the performance of the proposed method for detection and recognition of irregular craters in complex background.

KW - Contextual-based Hopfield neural network (CHNN)

KW - Crater detection

KW - Least median square ellipse

KW - Multi constraints

KW - Robust least square method

UR - http://www.scopus.com/inward/record.url?scp=84876073680&partnerID=8YFLogxK

U2 - 10.3873/j.issn.1000-1328.2013.03.004

DO - 10.3873/j.issn.1000-1328.2013.03.004

M3 - Article

AN - SCOPUS:84876073680

SN - 1000-1328

VL - 34

SP - 320

EP - 326

JO - Yuhang Xuebao/Journal of Astronautics

JF - Yuhang Xuebao/Journal of Astronautics

IS - 3

ER -

Detection and recognition method for irregular craters on planetary surface

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this