吉林大学学报(工学版) ›› 2003, Vol. ›› Issue (1): 1-7.

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Asphalt Pavement Surface Distress Image Recognition Based on Moment Invariant Feature

CHU Xiu-min, WANG Rong-ben, CHU Jiang-wei, WANG Chao   

  1. College of Transportation, Jilin University, Changchun 130025, China
  • Received:2002-05-13

Abstract: A method of image feature representation is put forward,which may reduce calculation of pavement surface distress image classification.Pavement surface image is divided into 64?64 pixels subimages,and greyness variances are used to represent subimages feature.Meanwhile,a subimage pattern classifier is designed based on BP artificial neural network,all classifying results of subimages pattern are arrayed in a matrix,which represents pavement surface distress image segmentation.Moment invariant of matrix is used to represent pavement distress image feature,and furthermore,a pavement distress forward feed neural network classifier is designed based on global optimization algorithm.Finally,pavement distress image recognition experiment is done,and accurately classifying rate is 83.3%.

Key words: pavement surface distress, model recognition, moment invariant, neural network

CLC Number: 

  • U416
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