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A Decision Support System for Face Sketch Synthesis Using Deep Learning and Artificial Intelligence.

Irfan Azhar¹, Muhammad Sharif¹, Mudassar Raza¹

¹Department of Computer Science, COMSATS University Islamabad, Wah Campus, Wah Cantt 47040, Pakistan.

Sensors (Basel, Switzerland)

|December 28, 2021

Summary

This summary is machine-generated.

This study introduces Spiral-Net, a novel deep learning model for generating face sketches from photos. This technology aids law enforcement in identifying suspects, improving accuracy by 5% over current methods.

Keywords:

NLDA OpenBR Spiral-Net U-Net Vgg-19 net convolutional neural network face recognition sketch synthesis smart cities

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Area of Science:

Computer Vision
Artificial Intelligence
Cybersecurity

Background:

The increasing crime rate necessitates advanced investigative tools.
Internet of Things (IoT) technologies offer potential for suspect identification.
Existing methods for face sketch synthesis using IoT and deep learning are limited.

Purpose of the Study:

To develop an improved deep learning architecture for face sketch synthesis.
To enhance suspect identification capabilities for law enforcement.

Main Methods:

A novel neural network architecture, Spiral-Net (a U-Net variant), was developed for face sketch synthesis.
Spiral-Net integrates with a pre-trained Vgg-19 network (feature extractor F) and a custom CNN (discriminator D).
The system identifies top sketch matches, formulates feature maps, and uses loss functions to iteratively update the networks.

Main Results:

The Spiral-Net model demonstrated a 5% improvement in face recognition accuracy compared to the state-of-the-art.
Performance was evaluated using datasets like CUFS, CUFSF, and IIT photo-sketch.
Results were validated against established face recognition schemes (NLDA and OpenBR).

Conclusions:

The proposed Spiral-Net architecture offers a significant advancement in face sketch synthesis.
This technology has strong potential for application in law enforcement and cybersecurity.
Further development could enhance its utility in combating cybercrime.