The measurement of foot size holds significant relevance across various domains, encompassing medical foot health assessments for evaluating foot well-being and advancing foot kinematics studies. Historically, limitations in measurement equipment and algorithms constrained the widespread adoption of 3D foot measurement techniques. However, leveraging novel methodologies integrating deep learning and image segmentation algorithms now enables swift and convenient foot measurements. Initially, a photograph capturing the user's foot alongside a standardized object is obtained, followed by the extraction of foot size and shape data from the image. The proposed methodology employs an Edge Detection Algorithm to delineate the edges of an A4 paper and employs traditional image segmentation algorithms to isolate the foot area.Encouragingly, the results demonstrate enhanced measurement speed and heightened accuracy in foot size assessment facilitated by the proposed algorithm.