Estimation of Feret's diameter from pixel coverage representation of a shape

被引：50

作者：

Drazic, Slobodan ^{[1
]}

Sladoje, Natasa ^{[2
,3
]}

Lindblad, Joakim ^{[2
,3
]}

机构：

[1] Univ Novi Sad, Fac Engn, Trg Dositeja Obradovica 6, Novi Sad 21000, Serbia

[2] Uppsala Univ, Ctr Image Anal, Box 337, S-75105 Uppsala, Sweden

[3] Serbian Acad Arts & Sci, Math Inst, Kneza Mihaila 36, Beograd 11000, Serbia

来源：

PATTERN RECOGNITION LETTERS | 2016年 / 80卷

关键词：

Feret's diameter; Coverage representation; Accuracy and precision; Shape analysis; DISTANCE; SEGMENTATION; ALGORITHMS; TRANSFORM;

D O I：

10.1016/j.patrec.2016.04.021

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Feret's diameter of a shape is a commonly used measure in shape analysis. Traditional methods for estimation of Feret's diameter are performed on binary images and are of poor precision and accuracy. We analyze and further develop a method for estimation of Feret's diameter that utilizes pixel coverage. We improve the accuracy of the method by proposing a correction term. We provide an expression for the upper bound of the absolute error of the estimation. We evaluate the improved method and compare with existing methods for Feret's diameter estimation, based on both binary and coverage representations of image objects. Tests confirm increased precision and accuracy of the new method, on synthetic as well as on real images. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：37 / 45

页数：9

共 20 条

[1]

Church T., 1968, Powder Technology, DOI [10.1016/0032-5910(68)80030-0, DOI 10.1016/0032-5910(68)80030-0]

[2] Efficient algorithm for finding the exact minimum barrier distance [J].

Ciesielski, Krzysztof Chris ;

Strand, Robin ;

Malmberg, Filip ;

Saha, Punam K. .

COMPUTER VISION AND IMAGE UNDERSTANDING, 2014, 123 :53-64

[3] Linear Time Algorithms for Exact Distance Transform [J].

Ciesielski, Krzysztof Chris ;

Chen, Xinjian ;

Udupa, Jayaram K. ;

Grevera, George J. .

JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2011, 39 (03) :193-209

[4]

Drazic S, 2011, INT SYMP IMAGE SIG, P569

[5] The image foresting transform: Theory, algorithms, and applications [J].

Falcao, AX ;

Stolfi, J ;

Lotufo, RDA .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2004, 26 (01) :19-29

[6]

Fouard C, 2006, LECT NOTES COMPUT SC, V4245, P259

[7] Anti-aliased Euclidean distance transform [J].

Gustayson, Stefan ;

Strand, Robin .

PATTERN RECOGNITION LETTERS, 2011, 32 (02) :252-257

[8] Machine vision based particle size and size distribution determination of airborne dust particles of wood and bark pellets [J].

Igathinathane, C. ;

Melin, S. ;

Sokhansanj, S. ;

Bi, X. ;

Lim, C. J. ;

Pordesimo, L. O. ;

Columbus, E. P. .

POWDER TECHNOLOGY, 2009, 196 (02) :202-212

[9] Coverage segmentation based on linear unmixing and minimization of perimeter and boundary thickness [J].

Lindblad, Joakim ;

Sladoje, Natasa .

PATTERN RECOGNITION LETTERS, 2012, 33 (06) :728-738

[10] A graph-based framework for sub-pixel image segmentation [J].

Malmberg, F. ;

Lindblad, J. ;

Sladoje, N. ;

Nystrom, I. .

THEORETICAL COMPUTER SCIENCE, 2011, 412 (15) :1338-1349

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