Abstract
This paper presents a simple Face Sketch-Photo Synthesis and Recognition system. Face Sketch Synthesis provides a way to compare and match the faces present in two different modalities (i.e. face-sketches and face-photos). The aim is to significantly reduce the differences between face-sketches and face-photos and also decrease the texture irregularity between them by converting photos to sketches and vice-versa. This results in effective matching between the two thus simplifying the process of facial recognition. This system is modeled using three major components: (i) For a given input face-photo, obtaining an output face-sketch. It is designed using image processing techniques like 2 scale image decomposition and color dodging. (ii) For a given input face-sketch, obtaining an output face-photo. Convolutional Neural Networks are used to model this component. (iii) For a given query face-sketch or face-photo, recognition of face-photo or face-sketch in the database. It is implemented using Fisherface Linear Discriminant Analysis.
Mitravinda, K.M., Chandana M., Monisha Chandra, Shaazin Sheikh Shukoor — Contributed equally to this work.
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Mitravinda, K.M., Chandana, M., Chandra, M., Shukoor, S.S., Mamatha, H.R. (2022). Face Sketch-Photo Synthesis and Recognition. In: Chen, J.IZ., Tavares, J.M.R.S., Shi, F. (eds) Third International Conference on Image Processing and Capsule Networks. ICIPCN 2022. Lecture Notes in Networks and Systems, vol 514. Springer, Cham. https://doi.org/10.1007/978-3-031-12413-6_7
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