LOW RESOLUTION FACE RECOGNITION USING DEEP LEARNING

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dc.contributor.authorBASNET, AARCHAN
dc.contributor.authorLAMICHHANE, BISHAL
dc.contributor.authorGURUNG, BISHWASH
dc.date.accessioned2023-07-30T06:09:04Z
dc.date.available2023-07-30T06:09:04Z
dc.date.issued2023-05
dc.descriptionIn many surveillance scenarios in real life, people may be far from the camera and their faces may be small in the field of view resulting in low resolution images. Such low resolution images can seriously degrade the performance of conventional face recognition systems which have been mainly developed for recognizing high quality images in controlled conditions.en_US
dc.description.abstractIn recent years, face recognition systems have achieved impressive performance and results using variety of algorithms and methods but such methods often fail to recognize a face image of low resolutiom. Face Recognition(FR) degrades when faces are of very low resolution since many details about the difference between one person and another can only be captured in images of sufficient resolution. In order to have better face recognition in low resolution environment, our project uses a Convolutional Neural Network(CNN) model of a Residual Network Architecture to reconstruct the low resolution image into a higher resolution image and another CNN model to extract features from the newly reconstructed image to compare and recognize the face using a classifier. In case of the project, the low resolution image is taken of resolution 32X32 and the higher resolution image is of 128X128. The PSNR value for the super resolution model is 29.3256 dB and SSIM value is 0.7686. The accuracy of the Face Recognition model is 86.32% The performance of proposed method is evaluated on a custom face dataset using confusion matrix and it shows a decent precision and recall values.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14540/18797
dc.language.isoenen_US
dc.publisherI.O.E. Pulchowk Campusen_US
dc.subjectLow Resolution(LR),en_US
dc.subjectHigh resolution(HR),en_US
dc.subjectSuper Resolution,en_US
dc.titleLOW RESOLUTION FACE RECOGNITION USING DEEP LEARNINGen_US
dc.typeReporten_US
local.academic.levelBacheloren_US
local.affiliatedinstitute.titlePulchowk Campusen_US
local.institute.titleInstitute of Engineeringen_US
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