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No-reference blur assessment of dermatological images acquired via mobile devices

: Vasconcelos, Maria Joao M.; Rosado, Luis


Elmoataz, A.:
Image and signal processing. 6th international conference, ICISP 2014 : Cherbourg, France, June 30 - July 2, 2014; Proceedings
Cham: Springer International Publishing, 2014 (Lecture Notes in Computer Science 8509)
ISBN: 978-3-319-07997-4 (Print)
ISBN: 978-3-319-07998-1 (Online)
International Conference on Image and Signal Processing (ICISP) <6, 2014, Cherbourg>
Fraunhofer AICOS ()
Mobile image assessment; Dermatology; Blur Distortion; Feature Extraction

One of the most important challenges of dealing with digital images acquired under uncontrolled conditions is the capability to assess if the image has enough quality to be further analyzed. In this scenario, blur can be considered as one of the most common causes for quality degradation in digital pictures, particularly in images acquired using mobile devices. In this study, we collected a set of 78 features related with blur detection and further analyzed its individual discriminatory ability for two dermatologic image datasets. For the dataset of dermoscopic images with artificially induced blur, high separation levels were obtained for the features calculated using DCT/DFT and Lapacian groups, while for the dataset of mobile acquired images, the best results were obtained for features that used Laplacian and Gradient groups.