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Development and Implementation of Graphical User Interface for Image Preprocessing using Matlab

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Shabari Shedthi B., Surendra Shetty, M. Siddappa

Shabari Shedthi B., Surendra Shetty and M Siddappa. Development and Implementation of Graphical User Interface for Image Preprocessing using Matlab. International Journal of Computer Applications 161(9):37-41, March 2017. BibTeX

	author = {Shabari Shedthi B. and Surendra Shetty and M. Siddappa},
	title = {Development and Implementation of Graphical User Interface for Image Preprocessing using Matlab},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {161},
	number = {9},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {37-41},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017913308},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Image pre-processing is a basic step for any image based applications. It is a technique to enhance quality of the images captured from cameras or sensors, aircrafts and space probes or pictures taken for various applications in normal day-to-day life. The accuracy of this technique must be significantly high in order to ensure the success of the subsequent steps. This intended software has the intention to make image preprocessing more efficient and interactive so that the user has clear idea about the outcome of each manipulation. In the intended application, one can manipulate the corrupted image to get the meaningful, desired output by applying various techniques provided in the software. The outcome of the intended application is obtained immediately and reduces the queue time to perform manipulations for the experienced user. If the user is a beginner, then he can go for trial session to try all the techniques and understand their outcome.


  1. Krishna Kant Singh, Akansha Singh, “A Study of Image Segmentation Algorithms for Different Types of Images”, IJCSI, vol. 7, Issue 5, Sep 2010.
  2. R. Krutsch, & D. Tenorio, “Histogram Equalization”, Freescale Semiconductor, Document Number AN4318, Application Note, Jun 2011.
  3. K. K Lavania, Shivali, R. Kumar, “Image Enhancement Using Filtering Techniques” International Journal on Computer Science and Engineering (IJCSE), vol. 4, No. 01, Jan 2012.
  4. Subhajit Adhikari, Joydeep Kar, Jayati Ghosh Dastidar,” An automatic and efficient foreground object extraction scheme”, International Journal of Science and Advanced Information Technology, Apr 2014.
  5. Ehsan Nadernejad, Sara Sharifzadeh, Hamid Hassanpour,” Edge Detection Techniques: Evaluations and Comparisons, Applied Mathematical Sciences”, vol. 2, no. 31, 1507 – 1520, Dec 2007
  6. Raman Maini and Himanshu Aggarwal,” Study and Comparison of Various Image Edge Detection Techniques, IJIP, vol. (3), Issue (1), Feb 2009.
  7. Kh. Manglem Singh, “Fuzzy Rule based Median Filter for Gray-scale Images”, Journal of Information Hiding and Multimedia Signal Processing, vol. 2, Number 2, Apr 2011.
  8. R. Oten and R. de Figueiredo,” Adaptive Alpha-Trimmed Mean Filters under Deviations from Assumed Noise Model”, IEEE Trans. Image Processing, vol. 13, No. 5, pp. 627-639,Apr 2004.
  9. H.A. Alshamarti, Ali K. Hussein, B.A. Almayahi, ”Application of median filter with the threshold technique to reduce and remove gaussian noise on the image edges produced by sobel operator”, International Journal Of Computer Engineering and Technology(IJET), vol. 4, Issue 6, Dec 2013.
  10. Mr. Salem Saleh Al-amri, Dr. N.V. Kalyankar and Dr. Khamitkar S.D, ”Deblured Gaussian Blurred Images”, Journal of computing, vol. 2, Issue 4, Apr 2010.
  11. Nida M.Zaitoun, musbah J. Aqel “survey on Image Segmentation Techniques”, International Conference on Communication, Management and Information Technology (ICCMIT), Elsevier, 2015
  12. Rafael C. Gonzalez, Richard E. Woods, “Digital Image Processing”, 2nd Ed. Beijing: Publishing House of Electronics Industry, 2007.
  13. Satish Kumar, Raghavendra Srinivas, “A Study on Image Segmentation and its Mae4dethods”, International Journal of Advanced Research in Computer Science and Software Engineering, vol. 3, Issue 9, Sep 2013.
  14. Nikita Sharma, Mahendra Mishra, Manish Shrivastava, “Colour Image Segmentation techniques and issues: an approach”, International Journal of Scientific & Technology Research vol. 1, Issue 4, May 2012.
  15. Sujata Saini and Komal Arora,”A Study Analysis on the Different Image Segmentation Techniques”, International Journal of Information & Computation Technology. ISSN 0974-2239 vol 4, Dec 2013.
  16. A.M Raid, W.M.Khedr, M.A.El-dosuky ,Mona Aoud, “Image Restoration Based on Morphological Operations”, International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.3, June 2014.


Image preprocessing; GUI (Graphical User Interface); Edge Detection; User Friendly Interface; Filters; Segmentation; Morphological Processing.