TY  - EJOU
AU  - Martis, Jason Elroy 
AU  - Shetty, Sannidhan Manjaya 
AU  - Pradhan, Manas Ranjan 
AU  - Desai, Usha 
AU  - Acharya, Biswaranjan 

TI  - Text-to-Sketch Synthesis via Adversarial Network
T2  - Computers, Materials \& Continua

PY  - 2023
VL  - 76
IS  - 1
SN  - 1546-2226

AB  - In the past, sketches were a standard technique used for recognizing offenders and have remained a valuable tool for law enforcement and social security purposes. However, relying on eyewitness observations can lead to discrepancies in the depictions of the sketch, depending on the experience and skills of the sketch artist. With the emergence of modern technologies such as Generative Adversarial Networks (GANs), generating images using verbal and textual cues is now possible, resulting in more accurate sketch depictions. In this study, we propose an adversarial network that generates human facial sketches using such cues provided by an observer. Additionally, we have introduced an Inverse Gamma Correction Technique to improve the training and enhance the quality of the generated sketches. To evaluate the effectiveness of our proposed method, we conducted experiments and analyzed the results using the inception score and Frechet Inception Distance metrics. Our proposed method achieved an overall inception score of 1.438 ± 0.049 and a Frechet Inception Distance of 65.29, outperforming other state-of-the-art techniques.
KW  - Generative adversarial networks; inverse gamma correction; sketch attributes; text-to-sketch synthesis; deep learning techniques

DO  - 10.32604/cmc.2023.038847