Image Quality Detection Using The Siamese Convolutional Neural Network

التفاصيل البيبلوغرافية
العنوان: Image Quality Detection Using The Siamese Convolutional Neural Network
المؤلفون: Milos Oravec, Ladislav Vizvary, Zuzana Bukovcikova, Dominik Sopiak
المصدر: 2019 International Symposium ELMAR.
بيانات النشر: IEEE, 2019.
سنة النشر: 2019
مصطلحات موضوعية: Artificial neural network, Biometrics, Computer science, Image quality, business.industry, media_common.quotation_subject, 0211 other engineering and technologies, Pattern recognition, 02 engineering and technology, Convolutional neural network, Image (mathematics), Identification (information), Identity (object-oriented programming), Quality (business), Artificial intelligence, business, 021101 geological & geomatics engineering, media_common
الوصف: It is an undeniable fact that image quality is closely related to the performance and accuracy of both verification and identification biometric systems. As an example, we can mention official documents, for instance passports or identity cards. Portraits in such documents must satisfy specific requirements in several categories. This paper describes our approach to determining the quality of images using artificial neural networks. We decided that we would use an approach different to most of the previously used ones - our system consists of two separate, but identical sub-networks, which together form a so called siamese neural network. The result of using such a network is that we are able to decide which one of a pair of images is of higher quality. As this paper later describes, the network can determine the better image in specific categories which affect the overall quality too.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::bb0ab085f4da76a027df1eb2c758701b
https://doi.org/10.1109/elmar.2019.8918678
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........bb0ab085f4da76a027df1eb2c758701b
قاعدة البيانات: OpenAIRE