Category Archives: PRJ702

Acknowledgements I would like to extend my thanks to the following, who have made this project a possibility: Dr David Ashton, my workplace supervisor in PFR for providing me with this opportunity, his time and his support. Without Ashton help, this project would not have been a possibility. To Jacky for all his time andContinue reading “Week 14 2020 06 05”

Performance of the fish eye extraction module and Future improvements. New images, provided by David, were used for the fish eye extraction performance. So in total there were two sets of data tested. Final version of the fish eye extraction module performance is good. It has a 100 % successful fish eye extraction rate onContinue reading “Week 13 2020 05 29”

Reference management software: Zotero Zotero is a very powerful reference management software to organize reference data such as research material and bibliographic. In my report, I have used so many references in different sources such as google scholar and web pages. Zotero is so use friendly. To add a reference to my reference library, IContinue reading “Week 12 2020 05 22”

I have writing up the report recently and faced several questions such as how to organize the report to let the reader understand what I did during the work placement. After finished first few sessions of the report, I show it to my supervisor Todd and he gave me advice of how to organize itContinue reading “Week 11 2020 05 15”

I have completed the outline of the project report and started to write up the report. The project report included 9 sections as below: Contents 1   Introduction 2   Background 3   Placement Plan 4   Placement Report 5   Placement Evaluation 6   Conclusion 7   References 8   Tables and Figures 9  Continue reading “Week 10 2020 05 08”

After finished version 3 of the fish eye pipeline, it is time to write up a documation of the pipeline.  The documentation I added is an implementation section that includes 4 parts and added to the readme of the repo. This can help users know how to setup and run the eye detection module.  ImplementationContinue reading “Week 9 2020 05 01”

Pipeline version 3 On version 2 the pipeline able to extract contour for all trevally images, however, only works on snapper imager with light colour. To overcome this problem and get the eye contour, I have tried two a approach: Adjust the contrast of the image and perform edge detection. convert the image to HLS andContinue reading “Week 7-8 2020 04 27”

I try to run my fish eye extraction pipeline on all trevally photos and only one-third of them working well. The reason could be the difference in background color and the fish have different patterns of color near the head area. There are 15 Trevally’s photos in my data set and can be divided intoContinue reading “Week 6 2020 04 17”

After the completion of the first version of the fish eye pipeline, I have get access of more data such as trevally, snapper images with different size and color background. However, because of the covid-19, PFR lockdown. I am not able to work in the facility and all of us need to prepare work distanceContinue reading “Week 4”

Outline of the first version of fish eye pipeline.    convert color image to grey scale    histogram correction to help even out colour    threshold image to binary    extract contours from thresholded image    filter contours to get round contours    filter contours to get largest circle Base on the above design, I create a pipeline and tried differentContinue reading “Week 3”