Full text: XVIIIth Congress (Part B3)

  
  
Recognizing Primitives Using Aspect-Interpretation Model Matching 
in A Both CAD and LP-based Measurement System 
Zhou Guoging 
Dept. of Computer Science and Technology, Tsinghua University, 
Beijing, 100084, P. R. China 
ABSTRACT 
In order to realize measuring automatically CAD-based object using line photogrammtery[3,4,6], 
the author in this paper presents recognizing primitive using model matching based on aspect- 
interpretation. The idea is composed of aspect-interpretation, aspect-graph(also called attribute 
relational graph) and model matching. The aspect-interpretation contains face-aspect code, face- 
aspect mergence code and face-aspect split code. The aspect-graph includes attribute relational 
graph, primitive attribute graph and attribute hypergraph. The model matching is to indicate 
matching model aspect-graph with image aspect-graph. Finally, the measurement system, which is 
an integration of CAD, Photogrammetry, Robot and CV, is briefly described. A group of 
. experiments is tested and the results show the recognition scheme is feasible. 
KEY WORDS: Recognition, Aspect-interpretation, Model matching, CAD, Line photogrammetry 
these schemes only recognize an object from 
1. INTRODUCTION 
After the author presented the idea that CAD- 
based industrial object can be measured using 
line photogrammetry(LP) so as to built up a 
bridge between CAD and CV system[3,4,6], a 
set of soft-package of LP for measuring various 
kind of primitives is developed. For the sake of 
automatic measurement, it is necessary to 
recognize automatically these primitives. In this 
paper, the author describe how to recognize the 
primitives in measurement system. 
Since the  model(data structure, strictly 
speaking, abstract model) of object has been 
stored in CAD system, recognizing primitives is 
in fact CAD-based model recognition. Many 
CAD-based recognition schemes have been 
proposed in papers published. Woo[18] used 
convex hull technique to describe the object. 
Kyprianou[13] applied syntactic pattern 
recognition methods to classify depression. 
Henderson[8] and  Kung[12] used logic 
programming and expert system to extract shape 
features. Joshi[9] developed attribute relational 
graphs for a part. Lee and Fu[14] proposed an 
algorithm for the exaction and unification of 
relatively complex scene. So, in all of the 
approaches above, they differ from recognizing 
single primitives from an object. Comparatively 
speaking, our recognition exists some characters 
as follows. 
e The primitives to be recognized are 
numbered. 
e Prior CAD information can be provided. 
In this paper, the author presents a novelty 
approach for recognizing different kind of 
primitives. Briefly, the contributions of this 
work can be summarized as follows. 
e Aspect-interpretation was presented to 
recognize some simple and regular primitives 
that lost less information in projection, as well as 
to assistantly construct aspect-graph. 
e The constructing regulation of aspect-graph 
based on aspect-interpretation was presented. 
e The data structure of model matching was 
studied 
e A measurement system was developed. 
2. ASPECT-INTERPRETATION 
PRINCIPLE 
some features from a CSG tree. Marefty[15] A 2-D image is perspective projection of 3-D 
used a geometric reasoning for recognition object, which consists of a number of primitives 
object. Most of these schemes adopted model by Boolean operator(unit, intersection, different) 
matching, however, previous methods have in CAD system. For this 2-D image, a number of 
limited success due to complex state of edges constructs a face in reasonable allocation 
projection in intersection, difference and way, and a number of faces forms a volume- 
emergence among primitives. Furthermore, primitive in reasonable allocation way, which 
1018 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B3. Vienna 1996 
   
   
   
  
  
  
  
  
  
  
   
   
   
     
  
  
  
  
   
    
   
      
  
  
  
   
      
    
   
  
    
   
    
    
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