Detection resizing images via SEAM carving using convolutional neural networks in computer forensics context

• Grant number: 16/25687-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2017
• End date: December 31, 2017
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Kelton Augusto Pontara da Costa
• Grantee: Luiz Fernando da Silva Cieslak
• Host Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil

Abstract

Seam carving is currently one of the most used methods to resize images. Its popularity is given by being a simple algorithm that maintains the content of the image. However, this technique is also used to remove objects and people from images, which can be a problem for Computational Forensics. The present proposal of scientific initiation aims at the creation of a seam carving process detection technique without having the knowledge of the original image, based on the image characteristics and image texture of properties provided by the Local Binary Pattern and using the Convolutional Neural Network techniques, which determines whether the image is original or changed by carving seam process. The proposed method of detection aims to serve as an aid to researchers in the field of computer forensics and cognitive computing, comparing its effectiveness with that of existing methods.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

DA SILVA CIESLAK, LUIZ FERNANDO; PONTARA DA COSTA, KELTON AUGUSTO; PAPA, JOAO PAULO; IEEE. Seam Carving Detection Using Convolutional Neural Networks. 2018 IEEE 12TH INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI), v. N/A, p. 5-pg., 2018-01-01. (13/07375-0, 14/12236-1, 16/25687-7, 16/19403-6)