Multi-modal biometric authentication system based on face and signature using legion feature estimation technique J. Vaijayanthimala 1 & T. Padma 2 Received: 22 March 2018 /Revised: 1 May 2019 /Accepted: 10 June 2019 # Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract In biometrics, picking of the right methodology is a testing errand for recognition of a person. Due to the advantage of widely accepted identification, face, and signature-based biometric modality are selected as a significant pattern as compared with other modalities. Different Face and signature successions of a similar subject may contain varieties in determination, light, pose, facial appearances and sign position. These varieties add to the difficulties in planning a viable multimodal-based face and signature recognition algorithm. This paper proposed about the face and signature recognition method from a large dataset with the different pose and multiple features. Face recognition is the first stage of a system then the signature verification will be done. Here, data glove signaling means of signing process are taken into account to do signature verification system. Hence the proposed work have used Face, and the corresponding signature is detected from data glove signal patterns to features-level fusion for the verification system. The proposed Legion feature based verification method will be developed using four important steps like, i) Preprocessing, ii) feature extraction from face and data glove signals, iii) Legion feature based feature matching through Euclidean distance, iv) Legion feature Neural network (LFNN) fusion based on weighted summation formulae where two weights will be optimally found out using Legion optimization algorithm, vi) Recognition based on the final score. Finally, based on the feature library the face image and signature can be recog- nized. The comparability estimation is finished by utilizing least Euclidean separation fusion based LFNN to decide perceived and non-perceived images. Also, in a similar examination, a proposed strategy is compared with current technique by several performance metrics and the proposed LFNN technique efficiently recognize the face images and corresponding signature from the input databases than the existing technology. Keywords LFNN . Recognition . Significant pattern . Multi-modal biometric . Legion feature estimation technique Multimedia Tools and Applications https://doi.org/10.1007/s11042-019-07871-z * J. Vaijayanthimala vaijayanthimala87@rediffmail.com Extended author information available on the last page of the article