The goal of quality assessment (QA) research is to design algorithms that can automatically assess the quality of images in a perceptually consistent manner. Image QA algorithms generally interpret image quality as fidelity or similarity with a “reference” or “perfect” image in some perceptual space. In order to improve the assessment accuracy of white noise, Gauss blur, JPEG2000 compression an...

Due to the recent challenges in access control, surveillance and security, there is an increased need for efficient human authentication solutions. Ear recognition appealing, where data acquisition procedure contactless, non-intrusive, covert. This article proposes a deep learning-based solution effective ear recognition. We explore multiple strategies enhance learning by using alternative data...

The performance of face analysis and recognition systems depends on the quality acquired data, which is influenced by numerous factors. Automatically assessing data in terms biometric utility can thus be useful to detect low-quality make decisions accordingly. This survey provides an overview image assessment literature, predominantly focuses visible wavelength input. A trend towards deep learn...