Multiscale data analysis for leather defect detection

Antonella Branca; Giovanni Attolico; Arcangelo Distante

doi:10.1117/12.257252

31 October 1996 Multiscale data analysis for leather defect detection

Antonella Branca, Giovanni Attolico, Arcangelo Distante

Proceedings Volume 2908, Machine Vision Applications, Architectures, and Systems Integration V; (1996) https://doi.org/10.1117/12.257252
Event: Photonics East '96, 1996, Boston, MA, United States

Abstract

The paper describes some early results obtained by applying a multiscale approach to texture analysis for effect detection on leather surfaces. Texture properties have proved to be a valuable help in characterizing the chaotic structures normally present on leather and the oriented structures typical of defects in spite of the wide range of associated visual appearances. Texture based defect detection can be done effectively by using the coefficients of the projection of a flow field into a vector space spanned by an appropriate basis function set. Being texture strongly related to scale we propose to extend the work of Rao and Schunck by employing a bank of filters, tuned at different scales, in order to perform the flow field estimation. Measures based on the coherence of outputs are used to determine at each point the scale providing the strongest oriented texture. Results showing the effect of synthesizing multiscale data into a single flow field will be provided.

Citation Download Citation

Antonella Branca, Giovanni Attolico, and Arcangelo Distante "Multiscale data analysis for leather defect detection", Proc. SPIE 2908, Machine Vision Applications, Architectures, and Systems Integration V, (31 October 1996); https://doi.org/10.1117/12.257252

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