International Journal of Computer-Aided Design and Applications

Abstract

In face recognition system implementation, human factors play a considerable role in the design and interpretation of remote sensing of images for pattern classification. Image sensing and cognition are the critical topics in image interpretation that bring together current state of art procedures which are widely recognised and tackled, especially in facial recognition image sensing with complex input data. It addresses most themes around expertise including the methods for knowledge acquisition and modelling of the expertise behind the modules and systems. This paper uses a facial recognition system at its production stage to test the model’s reliability and accuracy based on users’ subjective perception and real-time cognitive perception of the subjects used for the test procedure. Eighty people were interviewed while we took their skin conductance response (SCR) and they interacted in real-time with the window output of the facial recognition system, this is to obtain a subjective view of their cognitive response to the interface based on the best match of a particular face to its foreground image. The result shows that most participants considered the image fit to be above average match to the original greyscale image, and should not be part of feature classification for a facial recognition system.

Keywords: Face recognition system, Human cognition, Knowledge acquisition, Real-time cognitive perception, Skin conductance,  Cognitive response