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An ANN-Based Classification System for Automobile Parts with Different Shapes

  • Jihong Liu
  • GuangLu Zhao
  • Lingbo Kong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

In this paper, a system based on Artificial Neural Network (ANN) for classifying automobile parts with different shapes is presented. The system gets the original information from an image sensor, classifies two sorts of automobile parts with different shapes after processing these images. The classifier designed in this paper adopts the ANN with an improved BP algorithm. The perimeter, acreage and the degree of the decentralization of the automobile parts in the intensity image are taken as the input feature vectors. For the No.1 part and No.2 part, the experimental result indicates that the recognition accuracy rate can reach up to 99% in this system and the productivity will be improved obviously comparing with the checking result in the off-line system manually.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jihong Liu
    • 1
  • GuangLu Zhao
    • 1
  • Lingbo Kong
    • 1
  1. 1.College of Information Science and Engineering, Northeastern University, Shenyang 110004, LiaoningChina

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