  Considering the existence of very large amount of available data repositories
and reach to the very advanced system of hardware, systems meant for facial
identification ave evolved enormously over the past few decades. Sketch
recognition is one of the most important areas that have evolved as an integral
component adopted by the agencies of law administration in current trends of
forensic science. Matching of derived sketches to photo images of face is also
a difficult assignment as the considered sketches are produced upon the verbal
explanation depicted by the eye witness of the crime scene and may have
scarcity of sensitive elements that exist in the photograph as one can
accurately depict due to the natural human error. Substantial amount of the
novel research work carried out in this area up late used recognition system
through traditional extraction and classification models. But very recently,
few researches work focused on using deep learning techniques to take an
advantage of learning models for the feature extraction and classification to
rule out potential domain challenges. The first part of this review paper
basically focuses on deep learning techniques used in face recognition and
matching which as improved the accuracy of face recognition technique with
training of huge sets of data. This paper also includes a survey on different
techniques used to match composite sketches to human images which includes
component-based representation approach, automatic composite sketch recognition
technique etc.
