FACE RECOGNITION USING GENERALIZED ALMOST DISTRIBUTIVE FUZZY LATTICES IN IMAGE PROCESSING FOR FUZZY MORPHOLOGICAL EROSION

This paper explores face identification and recognition using MATLAB software,
implementing fuzzy morphological erosion based on Generalized Almost Distributive Fuzzy
Lattices (GADFL). Face recognition involves identifying a face biometric process used to identify
or verify a person by analyzing their facial features. The focus here is on recognizing faces
from binary images. Fuzzy morphological erosion is one of the most widely used fuzzy techniques
in image processing due to its foundation in distributive fuzzy lattices. This operation is
primarily applied to process various face reactions (binary images), where a partial ordering and
a fuzzy lattice structure are evident. Face recognition is achieved by analyzing intensity value
measurements of input images. The training dataset was compiled from various sources, incorporating
metrics such as Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR),
and the Structural Similarity Index (SSIM). The system demonstrated effective performance,
achieving an 80% recognition accuracy. MATLAB software was utilized for implementing the
proposed methodology."