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Procedia Computer Science 00 (2013) 000–000 www.elsevier.com/locate/procedia
Proceedings of the 4th International Conference on Computational Systems-Biology and Bioinformatics (CSBio 2013)
Preliminary Monitoring Barnacles growth Using SCILAB Programming (Image Processing) S.B.Ismaila, Salleh Z.b,*., M.Y.M.Yusopa, F.H.Fakhruradzia a
Universiti Kuala Lumpur Malaysian Institute of Marine Engineering Technology, Jalan Pantai Remis 32200 Lumut Perak, Malaysia b Centre of Excellence in Engineered Fibre Composites, University of Southern Queensland,Toowoomba QLD 4350, Australia
Extended Abstract
SCILAB image processing data is one of the options that analyses the image from digitised files [1]. In this research the photo of barnacle has been chosen to do analysis, image processing data is the best way to do an analysis on the engineering part, it also have a detail analysis shown from the photo. The image of barnacles was taken from the CITRA MOSTI boat made from the fibre-glass. The monitoring photos were taken within 3 months data. The results showed barnacle’s growth increased their size and quantity might be due to effect the saltwater characteristic. The results displayed with the SCILAB programming and analysed with comprehensive tabulated data. SCILAB has many collections of tool boxes suited for applications in science and technology fields. Image Processing Design Toolbox (IPD) is an image processing toolbox, which supports formats like BMP, PNG, JPEG, TIFF, and PBM [2]. SCILAB has many collections of tool boxes suited for applications in science and technology fields. Image Processing Design Toolbox (IPD) is an image processing toolbox, which supports formats like BMP, PNG, JPEG, TIFF, and PBM [3].Barnacle is a small saltwater animal with a protective shell-like covering show at Fig.1. There are more than 1,000 species. Barnacles on the hull of a ship increases the drag of the vessel, increase friction and can reduce the vessel’s speed. It also increases in fuel consumption to offset the higher friction. The ship must then be put in dry dock to have the bottom scraped. To prevent barnacles from clinging to ships, the hulls are either treated with toxic paint containing tin or copper or are coated with plastic. Almost all ships in the world are facing problems related to breeding Barnacles on the hull part.
* Corresponding author. Tel.: +(605) 6909000; fax: +(605) 6909091. E-mail address:
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S.B.Ismail/ Procedia Computer Science 00 (2013) 000–000
Fig. 1: Photo of Barnacles growth at hull boat
All the analyses data for three months are not much difference therefore result was presented at table 1. It is showed that image of barnacles for month December 2012 is started from real image, blob analyses, grey analyses, blue analyses and finally edge detection. From the results, its show that quantity of barnacles growth increasingly. It can be observed that barnacle’s growth was clearly detected by the blob analysis, it is to find the difference between the hull of the CITRA MOSTI and the Barnacle growth from the photo. This analysis comes out with three deference images Red, Grey and Blue (RGB) image [4]. When processing an image with a computer, it must be digitized or created in a digital format [5]. Table 1: Barnacles image for December 2012
Real Image
Blob Analyse
Grey Analyse
Blue Analyse
Edge Detection
The barnacles were changed their colour according to surface of hull boat. The connection among the live barnacles much closer to each other’s and can check their performance. If compared the colour image properties it’s clearly shows that photo December 2012 has good view might be effect due water quality. While photo edge detection shows the white colour that new barnacles g r e w a n d can d e t e r m i n e b y h i s t o g r a m u s i n g SCILAB programming. When using the blob analyses it is showed that all the photos can be determined by three colours mainly RED, GREY, BLUE also and called basic colour. From an above photo it can be seen the deference of three month of sample taken, the barnacles are start to growing up on the march, and the black colour is shown the barnacle, growth. Red image is intensity image, grey are greyscale and the blue is the filtered image. Objects can be found in a logical image by searching the connected areas of true pixels. The pixels of each connected area are mapped to an integer number greater than zero. All pixels of the same area have the same number whereas pixels belonging to different areas have different numbers. All false pixels are mapped to zero. Edge detection analysis is one of the main analyses in this study. The main purpose edge detection analysis is to define the edge of the barnacle growth from the sample photo taken. The difference of edge barnacle can see on the three samples taken, on the March 2013 photo can see the growing up of the barnacle from the edge detection. From the Edge detection analysis also it can be seen that the darker of image is more barnacle growth, on the March the grey colour is the peak of the barnacle it shown that the barnacle starting to growing up and full fill the area. It also shown the edge of the barnacle, on December 2012 the photo shown the barnacles are starting to grow and the March 2013 we can see the edges of barnacle are growing up.
S.B.Ismail/ Procedia Computer Science 00 (2012) 000–000
Based on the graph intensity histogram analyses, it shown the growth of the barnacle from December 2012, February 2013 and March 2013. Starting from December 2012 it only one peak of barnacle shown compare to the march 2013 it had a four peak shown the barnacle, the peak is the highest level of barnacle, it can be say that the barnacle are growing in a slow time. At Fig. 2 shows that on December 2012 graph show the only one peak of barnacle its mean that the barnacle are not full fill the hull of the CITRA MOSTI boat, the highest peak is about 2600 pixel high. At Fig. 3, on February 2013, shows that the result from graph there are 2 peaks of barnacle, from December 2012 it is only one peak and the February 2013 the barnacle had been growth, the highest maximum peak is about 3000 pixel more high before the December only 2600 pixel. The graph analysis that made for the photo March 2013, can be observed that the barnacle are starting to growth high, it shown that the March graph have a four peak, difference from December and February that only one and two peak. It also can say that the barnacle are growth about 10% from the first photo analysis, highest and maximum peak from the March 2013 graph analysis are about 3500 pixel more exceed than the December and February.
Fig.2: Graph Intensity Histogram on December 2012
Fig.3: Graph Intensity Histogram on February 2013
In summary, observation made based on three analyses result, it can be concluded that the growing up of the barnacle are approximately 10% of the 3 month sample photo taken. The growth of the barnacle cannot be control it depending on environment such as weather and seawater condition. It also needs a much time to do a periodically monitoring to know more specific on growth of the barnacle. SCILAB programing software is one the optional way to do a programing on image analysis, and need to explore as much as detail with the programing that can do it this SCILAB.
Acknowledgements The authors would like to acknowledge to Universiti Kuala Lumpur Malaysian Institute of Marine Engineering Technology for support and funding the Conference Grant and publication. References [1] Lena Mårtensson Lindblad and Björn Dahlbäck “Making Barnacles Walk Away” European Coatings Journal vol. 9, 2007, pp. 20-25. [2] Hema Ramachandran, “Image and Video Processing Toolbox in Scilab”, Journal of CSI Communication, 2012, pp 20-22. [3] Image Processing with Scilab and Image Processing Design Toolbox Copyright By Dr. Eng. (J) Harald Galda, 2011. [4]D. A. Forsyth, J. Ponce, Computer Vision: A Modern Approach, Prentice Hall Professional Technical Reference, 2002. [5]D. Brian Larkins1, William Harvey “Introductory computational science using MATLAB and image Processing” Procedia Computer Science 12010, pp 913–919.
© 2013 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of the Program Committee of CSBio2013.
