<p>There have been frequent advancements in the fields of object recognition, form matching, face recognition, and pattern recognition. Faces being a significant component of the human body, and there are several purposes for face detection, including security and forensic analysis. Key obstacles to face recognition are various facial expressions, illumination, position fluctuations, stance, occlusion, ageing, and resolution. Numerous approaches have been put forth in this area, but the algorithms may find it challenging to generalise and adapt to various situations and environments as a result of these factors. The aim of this paper is to introduce a face recognition technique using intuitionistic fuzzy set oscillation with the fractal theory in the Scale Invariant Feature Transform (SIFT) domain named IFO-FNDC. Intuitionistic fuzzy sets were introduced to handle complex circumstances ruled by uncertainty. In this paper, proposed face recognition consists of four parts: converting colour images to gray images, using SIFT to find key feature points, applying fractals to the face images to get the fractal values of the key points, and lastly, applying IF set oscillation for the comparison of known and unknown images. This proposed new face recognition algorithm was executed and experienced using MATLAB 2015a software on FacePix and FERET databases. The comparison of the results with several cutting-edge algorithms shows that IFO-FNDC performs better with excellent efficiency in runtime and accuracy rate.</p>