Content Based Image Retrieval based on Wavelet Transform coefficients distribution.

Mathieu Lamard (1) , Guy Cazuguel (1, 2) , Gwénolé Quellec (1, 2) , Lynda Bekri (3) , Christian Roux (1, 2) , Béatrice Cochener (1, 3)

1 LaTIM - Laboratoire de Traitement de l'Information Medicale
2 RSM - Département Réseaux, Sécurité et Multimédia
3 Service d'ophtalmologie [Brest]

In this paper we propose a content based image retrieval method for diagnosis aid in medical fields. We characterize images without extracting significant features by using distribution of coefficients obtained by building signatures from the distribution of wavelet transform. The research is carried out by computing signature distances between the query and database images. Several signatures are proposed; they use a model of wavelet coefficient distribution. To enhance results, a weighted distance between signatures is used and an adapted wavelet base is proposed. Retrieval efficiency is given for different databases including a diabetic retinopathy, a mammography and a face database. Results are promising: the retrieval efficiency is higher than 95% for some cases using an optimization process.

Domains: Bioengineering

Mathieu Lamard, Guy Cazuguel, Gwénolé Quellec, Lynda Bekri, Christian Roux, et al.. Content Based Image Retrieval based on Wavelet Transform coefficients distribution.. Conference proceedings : .. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2007, 1, pp.4532-5. ⟨10.1109/IEMBS.2007.4353347⟩. ⟨inserm-00189859⟩