Computer vision in forensic studies
The application of Computer Vision has been around since the 1960’s. However, due to the recent rise in popularity of Artificial Intelligence, the term has become more acclaimed in the industry. We have seen some forms of Computer Vision being used in our Surveillance Systems, Manufacturing lines, a...
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2021
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sg-ntu-dr.10356-1541312021-12-19T11:23:39Z Computer vision in forensic studies Sim, Jun Xian Seah Leong Keey School of Mechanical and Aerospace Engineering JM Vistec Systems Pte Ltd MLKSEAH@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Mechanical engineering The application of Computer Vision has been around since the 1960’s. However, due to the recent rise in popularity of Artificial Intelligence, the term has become more acclaimed in the industry. We have seen some forms of Computer Vision being used in our Surveillance Systems, Manufacturing lines, and even in social media. In this project, we aim to initiate the use of Computer Vision in an industry that has rather traditional protocol already in place – Forensic Studies. This project will focus its efforts to implement computer vision in a forensic testing/analysis station. The aim is to ease the color comparing process (e.g., Color Matching) at the same time, develop supporting vision systems (e.g., Head Detection, Position for Robotic Gripper), to create a constrained and quicker process for test kit analysis. The project will also include the development of a Graphical User Interface (GUI) to allow users to navigate through the different control variables for the individual vision system and to act as a user-friendly terminal for data acquisition. Additionally, the project will include the design and development of custom hardware built to constrain the data acquisition environment. Bachelor of Engineering (Mechanical Engineering) 2021-12-19T11:23:39Z 2021-12-19T11:23:39Z 2021 Final Year Project (FYP) Sim, J. X. (2021). Computer vision in forensic studies. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154131 https://hdl.handle.net/10356/154131 en C134 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Mechanical engineering Sim, Jun Xian Computer vision in forensic studies |
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The application of Computer Vision has been around since the 1960’s. However, due to the recent rise in popularity of Artificial Intelligence, the term has become more acclaimed in the industry. We have seen some forms of Computer Vision being used in our Surveillance Systems, Manufacturing lines, and even in social media. In this project, we aim to initiate the use of Computer Vision in an industry that has rather traditional protocol already in place – Forensic Studies. This project will focus its efforts to implement computer vision in a forensic testing/analysis station. The aim is to ease the color comparing process (e.g., Color Matching) at the same time, develop supporting vision systems (e.g., Head Detection, Position for Robotic Gripper), to create a constrained and quicker process for test kit analysis. The project will also include the development of a Graphical User Interface (GUI) to allow users to navigate through the different control variables for the individual vision system and to act as a user-friendly terminal for data acquisition. Additionally, the project will include the design and development of custom hardware built to constrain the data acquisition environment. |
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Seah Leong Keey |
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Seah Leong Keey Sim, Jun Xian |
format |
Final Year Project |
author |
Sim, Jun Xian |
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Sim, Jun Xian |
title |
Computer vision in forensic studies |
title_short |
Computer vision in forensic studies |
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Computer vision in forensic studies |
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Computer vision in forensic studies |
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Computer vision in forensic studies |
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computer vision in forensic studies |
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Nanyang Technological University |
publishDate |
2021 |
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https://hdl.handle.net/10356/154131 |
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1720447136788643840 |