Face detection is crucial in digital image processing for security applications. IoT safety concerns are increasing, and facial recognition under selective occlusion is a challenge. This study proposes a framework combining color and contour features with SVM and a sparse deep learning classification approach, achieving 98.5% face recognition accuracy and 96.5% occlusion verification accuracy. © 2022 Elsevier B.V., All rights reserved.