Camera model and processor identification based on eigen-regularization and extraction technique
In the world of mass media, problems with fraudulent images are frequent and troublesome. As such, image forensics has come a long way to ensure the authenticity and validity of images. However, the advancement in camera technology and image editing software has required more effort in the departmen...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2010
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| Online Access: | http://hdl.handle.net/10356/40518 |
| _version_ | 1811697045330722816 |
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| author | Chua, Li Fu. |
| author2 | Kot Chichung, Alex |
| author_facet | Kot Chichung, Alex Chua, Li Fu. |
| author_sort | Chua, Li Fu. |
| collection | NTU |
| description | In the world of mass media, problems with fraudulent images are frequent and troublesome. As such, image forensics has come a long way to ensure the authenticity and validity of images. However, the advancement in camera technology and image editing software has required more effort in the department of camera identification.
Using various tests and comparisons in this project, demosaicing features have been found to be the good choice for camera identification with low error rate and reasonable number of raw features. This project has also discovered that there are unique differences not just between camera manufacturers but also within the same brand, in this case, Canon.
It was found that there are some discriminant features between different generations of DIGIC image processor, as well as between models. It was also discovered that the accuracy of processor-based and model-based identification improves with the former and deteriorates with the latter, when multiple copies are being trained. |
| first_indexed | 2024-10-01T07:49:01Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/40518 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:49:01Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | ntu-10356/405182023-07-07T18:00:48Z Camera model and processor identification based on eigen-regularization and extraction technique Chua, Li Fu. Kot Chichung, Alex School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering In the world of mass media, problems with fraudulent images are frequent and troublesome. As such, image forensics has come a long way to ensure the authenticity and validity of images. However, the advancement in camera technology and image editing software has required more effort in the department of camera identification. Using various tests and comparisons in this project, demosaicing features have been found to be the good choice for camera identification with low error rate and reasonable number of raw features. This project has also discovered that there are unique differences not just between camera manufacturers but also within the same brand, in this case, Canon. It was found that there are some discriminant features between different generations of DIGIC image processor, as well as between models. It was also discovered that the accuracy of processor-based and model-based identification improves with the former and deteriorates with the latter, when multiple copies are being trained. Bachelor of Engineering 2010-06-16T04:11:48Z 2010-06-16T04:11:48Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/40518 en Nanyang Technological University 70 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Chua, Li Fu. Camera model and processor identification based on eigen-regularization and extraction technique |
| title | Camera model and processor identification based on eigen-regularization and extraction technique |
| title_full | Camera model and processor identification based on eigen-regularization and extraction technique |
| title_fullStr | Camera model and processor identification based on eigen-regularization and extraction technique |
| title_full_unstemmed | Camera model and processor identification based on eigen-regularization and extraction technique |
| title_short | Camera model and processor identification based on eigen-regularization and extraction technique |
| title_sort | camera model and processor identification based on eigen regularization and extraction technique |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | http://hdl.handle.net/10356/40518 |
| work_keys_str_mv | AT chualifu cameramodelandprocessoridentificationbasedoneigenregularizationandextractiontechnique |