No-reference Blur Assessment of Dermatological Images Acquired via Mobile Devices

  • Maria João M. Vasconcelos
  • Luís Rosado
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8509)


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.


Mobile image assessment dermatology blur distortion feature extraction 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Maria João M. Vasconcelos
    • 1
  • Luís Rosado
    • 1
  1. 1.Fraunhofer Portugal AICOSPortoPortugal

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