A constrained genetic algorithm for line labelling of line drawings with shadows and table-lines

被引:2
作者
Bonnici, Alexandra [1 ]
Camilleri, Kenneth P. [1 ]
机构
[1] Univ Malta, Fac Engn, Dept Syst & Control Engn, Msida, Malta
来源
COMPUTERS & GRAPHICS-UK | 2013年 / 37卷 / 05期
关键词
Line labelling; Genetic algorithms; Cast shadows; Attached shadows; Table-lines; CURVED OBJECTS; 3D OBJECT; OPTIMIZATION; RECONSTRUCTION;
D O I
10.1016/j.cag.2013.01.008
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Line drawings are well known to exhibit geometric ambiguities, resulting in, drawings that can have multiple interpretations. However, drawings are used to present design concepts to peers in fields such as engineering design, where it is imperative that the observer interprets the drawing in the same way as the designer for effective communication. Designers therefore use cues, prompting the observer to resolve the geometric ambiguities and achieve the desired interpretation. In this paper, we identify the cues introduced in drawings and focus on two cues, namely table-lines (which convey information about the position of the object in space) and shadows (which convey information about the geometry of the object). These cues can be used in a line-labelling context to allow a line-labelling algorithm to overcome the geometric ambiguities of the drawing. For this purpose, we propose a cue-constrained genetic algorithm that takes the vectorized line drawing and the identified cues attached to each edge, and uses these cues as constraints on the edge labels, thus distinguishing between different object-background interactions. We show that the proposed algorithm can be used to successfully label intentionally ambiguous line drawings according to some desired interpretation as specified by the additional cues present in the drawing. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:302 / 315
页数:14
相关论文
共 30 条
[1]  
[Anonymous], 2000, Visual Intelligence: How We Create What We See
[2]  
[Anonymous], 1975, The Psychology of Computer Vision
[3]  
Bonnici A, 2012, P INT S SKETCH BAS I, P77
[4]  
Bonnici A, 2012, P 7 INT C THEOR APPL
[5]  
Clowes MB, 1971, ARTIF INTELL, V2, P76
[6]  
Company P, 1999, 2 SEM IT ESP DIS FAB, P3
[7]  
Cooper M., 2008, LINE DRAWING INTERPR
[8]   A rich discrete labeling scheme for line drawings of curved objects [J].
Cooper, Martin C. .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2008, 30 (04) :741-745
[9]   The interpretation of line drawings with contrast failure and shadows [J].
Cooper, MC .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2001, 43 (02) :75-97
[10]  
Eiben A. E., 2015, Natural computing series