Week 1:
After my internship with Intel, I have chosen the topic propose from a list of potential projects for final year project given by internship supervisor which is “Design and implementation of an embedded NIOS II system for fractal image decoder”. These are the questions ask based on the activity summary list.
- Why is this a project to begin with?
- This project is developing a new fractal image decoder with a faster processing time using NIOS II system.
- What are the things you want to improve?
- I would like to improve the speed of the decoding process of the fractal image.
Week 2:
In week 2, I had attended the Online Research Methodology Workshop. In this workshop, they start with sharing the YouTube link on Research Methodology conducted by UTM last year that we can watch. Then, the back part of this Workshop was mostly mentioned about the Innovate Malaysia Design Competition. For my Final Year Project title, I had set the goals and major deliverables of this project.
- What are the goals of your project?
- To have a fast decoding system for fractal image decoder by using NIOS II system.
- What are the major deliverables/contributions of this project?
- Major contribution would be everyone can have a faster system to complete the fractal image decoding.
Week 3:
To make sure my project can be done with a smoother flow, the question had been answered to have a further understanding in the project.
- What purpose does the work serve, what is the end-goal?
- The work serves are to allow user can do the fractal image decoding with faster processing time. The end-goal will be providing user have the platform or coding with a user-friendly fractal image decoder.
- What should be done at this early stage to ensure fewer risks and obstacles during the course of the project?
- Doing research on the article to get more understand about what fractal image is and how does fractal image work.
- Do some research on NIOS II system.
- Study on the research article to get more idea to design this project.
- What are the major steps in the project plan?
- Decide the FPGA that will be used in the project.
- Think the best way to shorter the time spending to complete the fractal image decoding.
Week 4:
To continue for planning my Final Year Project, I had done some reading on few articles to figure out the potential research problems.
- Identify three potential research problems of interest.
- Decoding and encoding process of the fractal image.
- Improvement of the time spend on the fractal image decoding.
- Monitoring the output after the decoding process.
- Write a possible research question for each of above problems.
- How does decoding and encoding of fractal image wok?
- How to improve the time spend of the fractal image decoding.
- How to confirm the output of the result is correct?
- Write possible hypothesis for each of the above research questions.
- Do some research on decoding and encoding.
- Using NIOS II system to improve the time spend of the fractal image decoding.
- Use the output as the input for fractal image encoding to compare the original input.
Week 5:
To get some background information on how to Design and implementation of an embedded NIOS II system for fractal image decoder, I did some research on some article on the internet from Google Scholar.
During Week 5, I reviewed 5 papers related to fractal image.
Front the first article with title “A review of the fractal image coding literature” by B. Wohlberg and G. De Jager. (1999). From this article mention that Fractal image compression is a technique based on the representation of an image by a contractive transform, on the space of images, for which the fixed point is close to the original image. This broad principle encompasses a very wide variety of coding schemes, many of which have been explored in the rapidly growing body of published research. Most purely fractal-based schemes are not competitive with the current state of the art, but hybrid schemes incorporating fractal compression and alternative techniques have achieved considerably greater success.
In the next article I reviewed with title “Fractal Image Coding: A Review” by Arnaud E. Jacquin. (1993). It states that the main characteristics of this approach are that it relies on the assumption that image redundancy can be efficiently captured and exploited through piecewise self-transformability on a block-wise basis, and it approximates an original image by a fractal image, obtained from a finite number of iterations of an image transformation called a fractal code. This approach is referred to as fractal block coding.
Third article I had refer is “Fractal Image Compression” by Michael F. Barnsley (1996). From this article, it states that fractal image compression evolved from the mathematical ferment on chaos and fractals in the years 1978–1985 and on the resurgence of interest in Julia sets and dynamical systems.
In the fourth article I reviewed is “Technique for fractal image compression using genetic algorithm” by S, K. Mitra et al. It states A new method for fractal image compression is proposed using genetic algorithm (GA) with an elitist model. The self-transformation property of images is assumed and exploited in the fractal image compression technique. The technique described utilizes the GA, which greatly decreases the search space for finding the self-similarities in the given image.
In the last article that been reviewed in this week is “Speed-Up In Fractal Image Coding Comparison of Methods” by Mario Polvere and Michele Nappi (2000). In this article, they introduce two new coding schemes combining Saupe with Fisher, and Saupe with mass center coding scheme. Experimental results demonstrate both the superiority of feature vector techniques on classification and the effectiveness of combining Saupe and the mass center coding scheme, an approach that exhibits the best time-distortion curves.