dc.creator | Najem M.F., Elmansouri | |
dc.date | 2018 | |
dc.date.accessioned | 2023-09-05T02:10:41Z | |
dc.date.available | 2023-09-05T02:10:41Z | |
dc.identifier.uri | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/79136 | |
dc.description | Master of Science in Embedded System Design Engineering | en_US |
dc.description.abstract | An image contains large size of digital data and it is necessary to reduce digital data volume by using image compression method in order to reduce storage size and reduce data transmission time. This project mainly concentrates on image compression using a low cost Raspberry Pi board. The purpose of this project is to preserve a large number of information in the images and retaining its quality compare with PC based method. Haar transform is a family of wavelet image compression where the raw image is transformed to the other domain to produce smaller size of data. Wavelet transform has low computational complexity and fast processing algorithm. In this project, wavelet transform based on Haar is implemented using Raspberry Pi single board computer running on an ARM based processor. The raspberry Pi board has an advantage of image processing implementation due to the existing of software development tool offered a rich feature for image processing such as OPENCV and Numpy libraries. The project consists of several design stages such as image pre-processing, the development of Haar algorithm, error rate computation and measurement by PSNR and MSE. The algorithm is developed using Python programming language with the additional image processing library such as OpenCV and NumPy mathematical library. The compression algorithm is tested on several biometric images such as face and fingerprint images. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universiti Malaysia Perlis (UniMAP) | en_US |
dc.rights | Universiti Malaysia Perlis (UniMAP) | en_US |
dc.subject | Image compression | en_US |
dc.subject | Raspberry Pi (Computer) | en_US |
dc.title | Wavelet image compression implemented using Raspberry PI | en_US |
dc.type | Dissertation | en_US |
dc.contributor.advisor | Muhammad Imran, Ahmad, Dr. | |
dc.publisher.department | School of Computer and Communication Engineering | en_US |