Geometric feature recognition: Coping with the complexity and infinite variety of features

1999 ◽  
Vol 12 (5) ◽  
pp. 439-452 ◽  
Author(s):  
C. F. Yuen ◽  
Patrik Venuvinod
Keyword(s):  
Feature Recognition ◽  
Geometric Feature ◽  
Infinite Variety

The Geometrical Feature Recognition Method of Part Drawing

2011 ◽  
Vol 415-417 ◽  
pp. 523-526
Author(s):  
Yan Dong ◽  
Mei Li
Keyword(s):  
Feature Recognition ◽  
Graph Matching ◽  
Geometric Feature ◽  
Recognition Method ◽  
Recognition Mechanism ◽  
Chemical Database ◽  
Geometry Feature ◽  
Constraint Structure ◽  
Geometric Elements ◽  
Fine Tune

This paper put forward a geometry feature recognition method of part drawing based on graph matching. Describe the constraints structure of geometric feature in geometric elements and those constraint relationships. Match sub-graph in contour closure graphics and those combination. Using linear symbol notation of chemical compounds in chemical database for reference, encode to constraint structure of geometry graphics, establish recognition mechanism of geometric characteristics by structure codes. Taking the fine-tune screw and fork parts for example, this method has been proved to be effective.

Research and Development of Micro-Hole Quality Detecting System Based on Machine Vision

2013 ◽  
Vol 694-697 ◽  
pp. 1902-1905
Author(s):  
Hui Tao Cai ◽  
Qiu Ju Xiong ◽  
Yong Liu
Keyword(s):  
Feature Recognition ◽  
Median Filter ◽  
Threshold Value ◽  
Least Square ◽  
Geometric Feature ◽  
Quality Inspection ◽  
Hole Quality ◽  
Micro Hole ◽  
Processing Techniques ◽  
Roundness Measurement

An effective approach of quality inspection for micro hole is proposed by studying on the geometric feature of micro hole edge. The edge of micro hole is detected exactly with the digital image processing techniques, such as, the median filter, the threshold value transformation, and so on. The least square circle fit arithmetic and a new roundness measurement arithmetic are synthetically used in the processing of geometric feature recognition of micro hole. The practical results prove that the method with exact conclusion and high precision can satisfy the quality inspection requirement of micro hole.

Efficient Automated Geometric Feature Recognition through Feature Coding

CIRP Annals ◽  
1994 ◽  
Vol 43 (1) ◽  
pp. 413-416 ◽  
Author(s):  
P.K. Venuvinod ◽  
C.F. Yuen ◽  
M.E. Merchant
Keyword(s):  
Feature Recognition ◽  
Geometric Feature

Geometric Feature Recognition by Object Decomposition

1989 ◽  
Author(s):  
C. Karra ◽  
T. A. Phelps
Keyword(s):  
Feature Recognition ◽  
Geometric Feature ◽  
Design Tools ◽  
Solid Object ◽  
Solid Modelling ◽  
New Approach ◽  
Design Engineers ◽  
Manufacturing Information ◽  
Computer Based ◽  
Analysis Design

Abstract Design engineers have traditionally have had inadequate manufacturing information. One method of getting that information to them is through its inclusion in computer-based design tools such as geometric solid modelling programs. Analysis of geometry requires methods such as feature recognition. A new approach to feature recognition has been developed which recognizes features by taking apart the original solid object into prismatic primitives. This approach already covers a very large portion of what is currently manufactured. The expected applications of this approach include automatic manufacturability analysis, design for assembly, process planning, etc.

Development of Quality Detecting System for Micro Holes by ECM Based on Machine Vision Technology

2013 ◽  
Vol 397-400 ◽  
pp. 1482-1485 ◽  
Author(s):  
Yong Liu ◽  
Lin Sen Zhu ◽  
Qiu Ju Xiong
Keyword(s):  
Feature Recognition ◽  
Detection System ◽  
Electrochemical Machining ◽  
Threshold Value ◽  
Least Square ◽  
Geometric Feature ◽  
Quality Detection ◽  
Micro Holes ◽  
Micro Hole ◽  
Processing Techniques

A rapid quality detection system for micro hole fabricated by electrochemical machining (ECM) is proposed by studying on the optical features of micro hole. The edge of micro hole is detected exactly with the digital image processing techniques, such as, the middle value filter, the threshold value transformation, and so on. The least square circle fit arithmetic and the new roundness measurement algorithm are synthetically used in the processing of geometric feature recognition of micro holes. The practical results prove that the method with exact conclusion and high precision can satisfy the quality inspection requirement of micro holes fabricated by ECM.

Novel method of regional facial geometric feature recognition to Chinese human face

2003 ◽  
Author(s):  
Weiguo Gong ◽  
Jiamin Liu ◽  
Weihong Li ◽  
Yingjun Pan ◽  
Hongmei Zhang
Keyword(s):  
Feature Recognition ◽  
Geometric Feature ◽  
Human Face ◽  
Novel Method

Research on Optical Feature Recognition Technology of Multiple Micro-Holes

2014 ◽  
Vol 852 ◽  
pp. 373-377 ◽  
Author(s):  
Hui Tao Cai ◽  
Yong Liu
Keyword(s):  
Feature Recognition ◽  
Detection System ◽  
Electrochemical Machining ◽  
Least Square ◽  
Geometric Feature ◽  
Fast Detection ◽  
Quality Detection ◽  
Micro Holes ◽  
Micro Hole ◽  
Processing Techniques

A rapid quality detection system for multiple micro-holes fabricated by electrochemical machining (ECM) is proposed by studying on the optical features of multiple micro-holes. First, the edge of multiple micro-holes is detected exactly with the digital image processing techniques. Second, the multiple micro-holes are recognized through image skeleton extraction and region segmentation algorithm. Then, the least square circle fit arithmetic; the new roundness measurement algorithm and the surface roughness measurement method are synthetically used in the processing of geometric feature recognition of each micro hole. Finally, the practical results prove that the rapid quality detection system is provided with a fast detection speed and high precision for meeting the quality inspection requirement of multiple micro-holes.

Defects’ geometric feature recognition based on infrared image edge detection

2014 ◽  
Vol 67 ◽  
pp. 387-390 ◽  
Author(s):  
Liu Junyan ◽  
Tang Qingju ◽  
Wang Yang ◽  
Lu Yumei ◽  
Zhang Zhiping
Keyword(s):  
Edge Detection ◽  
Feature Recognition ◽  
Infrared Image ◽  
Geometric Feature ◽  
Image Edge Detection ◽  
Image Edge
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