Smart Recognition and Authentication based on Haar Cascade Classifier and Visual Cryptography

The algorithm with an E-verification method is proposed that combines automated facial recognition technology with digital media and later it combines aspects of secret data exchange and visual cryptography. A face detection technique based on Internet of Things (IoT) selects features using the Principal Component Analysis (PCA) algorithm and the Haar cascade classifier. The selected face serving as a cover follows two level Discrete Haar Wavelet Transform. The shares generated from digital signature and fingerprint are diffused into the converted coefficients. Furthermore, the imperceptibility of the additional noise is increased by a bit-level noise reduction technique. Authenticity is confirmed by regenerating a message digest at the receiving end, and the extraction process operates in complete blindness. The approach is suitable for smart card design and may be used as an automatic recognition system in a real-world setting. Performance comparisons show a notable improvement over other approaches that are comparable. Additionally, the technique is effective against some related attacks.