Object recognition using relative-chord context

Hua Chai (1) , Mingqiang Yang (1) , Kidiyo Kpalma (2) , Joseph Ronsin (2)

1 ISE - School of Information Science and Engineering
2 IETR - Institut d'Electronique et de Télécommunications de Rennes

In this paper the relative-chord context is proposed for shape description in object recognition. The relative-chord is introduced to obtain the affine-invariant feature. The intervals of parallel chords are normalized by vertical direction-chord. Experimental result based on the Columbia University Coil-100 3D database demonstrates the feasibility of the relative-chord context methodology and also highlights its invariance to affine transforms.

Mots clés: relative-chord; correlation statistics; object recognition; affine transformation

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Hua Chai, Mingqiang Yang, Kidiyo Kpalma, Joseph Ronsin. Object recognition using relative-chord context. International Conference on Consumer Electronics, Communications and Networks (CECNet), Apr 2011, Jinan, China. pp.515-518, ⟨10.1109/CECNET.2011.5768917⟩. ⟨hal-00652951⟩