Open Access   Article Go Back

Analysis of Various Image Preprocessing Techniques for Denoising of Flower Images

Isha Patel1 , Sanskruti Patel2 , Atul Patel3

  1. Faculty of Computer Science and Applications, Charotar University of Science and Technology, Changa, India.
  2. Faculty of Computer Science and Applications, Charotar University of Science and Technology, Changa, India.
  3. Faculty of Computer Science and Applications, Charotar University of Science and Technology, Changa, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 1111-1117, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.11111117

Online published on May 31, 2018

Copyright © Isha Patel, Sanskruti Patel, Atul Patel . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Isha Patel, Sanskruti Patel, Atul Patel, “Analysis of Various Image Preprocessing Techniques for Denoising of Flower Images,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1111-1117, 2018.

MLA Style Citation: Isha Patel, Sanskruti Patel, Atul Patel "Analysis of Various Image Preprocessing Techniques for Denoising of Flower Images." International Journal of Computer Sciences and Engineering 6.5 (2018): 1111-1117.

APA Style Citation: Isha Patel, Sanskruti Patel, Atul Patel, (2018). Analysis of Various Image Preprocessing Techniques for Denoising of Flower Images. International Journal of Computer Sciences and Engineering, 6(5), 1111-1117.

BibTex Style Citation:
@article{Patel_2018,
author = {Isha Patel, Sanskruti Patel, Atul Patel},
title = {Analysis of Various Image Preprocessing Techniques for Denoising of Flower Images},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {1111-1117},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2116},
doi = {https://doi.org/10.26438/ijcse/v6i5.11111117}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.11111117}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2116
TI - Analysis of Various Image Preprocessing Techniques for Denoising of Flower Images
T2 - International Journal of Computer Sciences and Engineering
AU - Isha Patel, Sanskruti Patel, Atul Patel
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 1111-1117
IS - 5
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
1004 480 downloads 291 downloads
  
  
           

Abstract

Identification, and classification of flower images is a crucial issue faced by academicians and researchers. The manual process to distinguish different flower images is a complex task and found difficult for novice persons. A process of extraction, analysis, and understanding of useful information from images is accomplished by an automated process using Computer vision. It basically aims to model, replicate and exceed human vision using computer hardware and software. Image processing techniques may help to recognize a flower image for further identification and classification of them in different species. The fundamental step in image processing is image preprocessing that is applied to improve the quality of images and removing the irrelevant noises existed in images. This paper represents a comparative analysis of different image preprocessing techniques implemented on flower images. The performance evaluation of these techniques is based on their potential to remove noise in flower images. For performance evaluation, Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE) methods are used.

Key-Words / Index Term

Image processing, Image preprocessing techniques, PSNR, RMSE

References

[1] Nisha, Isha, “A Survey on Different Classification Methods on Agricultural Processing”, Journal of Network Communications and Emerging Technologies (JNCET), Volume 3, Issue 1, pp.68-72, July 2015.
[2] Chomtip Pornpanomchai, Ponrath Sakunreraratsame, Rosita Wongsasirinart, Nuttakan Youngtavichavhart, “Herb Flower Recognition System (HFRS)”, IEEE, Volume 1, pp. V1-123-V1-127, 02 September 2010
[3] Warisara Pardee, Prawaran Yusungnern, Peeraya Sripian, “Flower Identification System by Image Processing”, Researchgate, August 2015
[4] Y H Sharath Kumar, N Vinay Kumar, D S Guru, “Delaunay Triangulation on Skeleton of Flowers for Classification”, International Conference on Advanced Computing Technologies and Applications (ICACTA), Volume 45, Issue, C, pp. 226 – 235, 2015
[5] Fadzilah Siraj, Hawa Mohd Ekhsan, Abdul Nasir Zulkifli, “Flower Image Classification Modeling Using Neural Network”, International Conference on Computer, Control, Informatics and Its Applications, pp. 81-86, 2014.
[6] Janani, R & Gopal, A. (2013). Identification of selected medicinal plant leaves using image features and ANN. Proceedings of the 2013 International Conference on Advanced Electronic Systems, ICAES 2013. 238-242. 10.1109/ICAES.2013.6659400.
[7] I.Kiruba Raji, K.K.Thyagharajan, “An Analysis of Segmentation Techniques to Identify Herbal Leaves from Complex Background”, International Conference on Intelligent Computing Communication and Convergence (ICCC), Science Direct, Volume 48, pp. 589-599, 2015.
[8] Kim, Yeong-Taeg. (1997). Kim, Y.T.: Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Trans. Consum. Electron. 43(1), 1-8. Consumer Electronics, IEEE Transactions on. 43. 1 - 8. 10.1109/30.580378.
[9] Angela. Saibahu, and K. Vijayan Asari. “An Adaptive and Non-Linear Technique for Enhancement of Extremely High Contrast Images.”, In Applied Imagery and Pattern Recognition Workshop, 35th IEEE, pp. 24-24, 2006.
[10] Cheng, H. D., and Yingtao Zhang. “Detecting of contrast over-enhancement’, In Image Processing (ICIP), 19th IEEE International Conference on, pp. 961-964, 2012.
[11] X. Chen and L. Lv, "A Compositive Contrast Enhancement Algorithm of IR Image", International Conference on Information Technology and Applications (ITA), Chengdu, China, IEEE, pp.58-62, 2013.
[12] Sundaram, M., K. Ramar, N. Arumugam, and G. Prabin. "Histogram-based contrast enhancement for mammogram images.", In Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), 2011 International Conference on, pp. 842-846. IEEE, 2011.
[13] Ayushi Jaiswal, Jayprakash Upadhyay, Ajay Somkuwar, “Image denoising and quality measurements by using filtering and wavelet-based techniques”, International Journal of Electronics and Communications (AEU), ScienceDirect, Volume 68, Issue 8, pp. 699-705, August 2014.
[14] Chandrika Saxena, Prof. Deepak Kourav, “Noises and Image Denoising Techniques: A Brief Survey”, International Journal of Emerging Technology and Advanced Engineering, Volume 4, Issue 3, pp.878-885, March 2014.
[15] Meenal Jain, Sumit Sharma, Ravi Mohan Sairam, “Effect of Blur and Noise on Image Denoising based on PDE”, International Journal of Advanced Computer Research (IJACR), Volume-3, Issue-8, pp. 236-241, March-2013.
[16] Meenal Jain, Sumit Sharma, Ravi Mohan Sairam, “Result Analysis of Blur and Noise on Image Denoising based on PDE”, International Journal of Advanced Computer Research (IJACR) Volume-2, Issue-7, pp. 70-77, December-2012.
[17] S.S. Agaian, K.P. Lentz, A.M. Grigoryan,” A New Measure of Image Enhancement”, International Conference on Signal Processing & Communication, pp. 19–22, 2000.
[18] Dr.K.Thangadurai, K.Padmavathi, “Computer Vision image Enhancement for Plant Leaves Disease Detection”, World Congress on Computing and Communication Technologies, IEEE, pp. 173-175, 2014.
[19] C.Ananthi, Azha.Periasamy, S.Muruganand, “Pattern Recognition of Medicinal Leaves Using Image Processing Techniques”, Journal of Nano Science and Nanotechnology, Volume 2, Issue 2, pp.214-218, February 2014.
[20] K. Padmavathi and K. Thangadurai,” Implementation of RGB and Grayscale Images in Plant Leave Disease Detection – Comparative Study”, Indian Journal of Science and Technology, Volume 9(6), pp.1-6, February 2016.
[21] Mr. Salem Saleh Al-Amri, Dr.N.V.Kalyankar, Dr.S.D.Khamitkar, “Linear and Non-linear Contrast Enhancement Image”, International Journal of Computer Science and Network Security (IJCSNS), Volume 10, No.2, pp. 139-143, February 2010.
[22] Pooja and Gurwinder Singh Jatana, “Adaptive histogram equalization technique for enhancement of colored image quality”, International Journal of Latest Trends in Engineering and Technology, Volume 8, Issue 2, pp.010-017, March 2017.
[23] M.Mallika, Dr. J. Jebakumari Beulah Vasanthi, “Image Enhancement Techniques on Plant Leaf and Seed Disease Detection,” International Journal of Innovative Research in Computer and Communication Engineering, Volume 5, Special Issue 1, pp. 109-116, March 2017.
[24] Deepak J. Dange and Prof. M. A. Sayyad, “Computer Vision Image Enhancement and Plant Leaves Disease Detection”, International Journal of Modern Trends in Engineering and Research (IJMTER), Volume 02, Issue 06, pp. 106-110, June 2015.
[25] Mohd. Junedul Haque, “A Brief Review of Image Restoration Techniques”, International Journal of Advanced Computing Research, Volume 01, pp. 42-45, 2014.
[26] Monika Maru, M. C. Parikh, “Image Restoration Techniques: A Survey”, International Journal of Computer Applications, Volume 160, pp. 15-19, February 2017.
[27] H. Salome Hema Chitra, S. Suguna, and S. Naganandini Sujatha, “A Survey on Image Analysis Techniques in Agricultural Product”, Indian Journal of Science and Technology, Volume 9(12), pp. 1-13, March 2016.
[28] Gursharan Kaur, Rakesh Kumar, Kamaljeet Kainth, “A Review Paper on Different Noise Types and Digital Image Processing”, International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), Volume 6, Issue 6, pp. 562-565, June 2016.
[29] Inderpreet Singh, Nirvair Neeru, “Performance Comparison of Various Image Denoising Filters under Spatial Domain”, International Journal of Computer Applications, Volume 96-No.19, pp. 21-30, June 2014.
[30] Govindaraj.V, Sengottaiyan.G, “Survey of Image Denoising using Different Filters”, International Journal of Science, Engineering and Technology Research (IJSETR), Volume 2, Issue 2, pp. 344-351, February 2013.
[31] Sandeep Kumar Agarwal and Prateek Kumar, “Denoising of A Mixed Noise Color Image through Special Filter”, International Journal of Signal Processing, Image Processing, and Pattern Recognition, Volume 9, No.1, pp.159-176, 2016.
[32] Sheikh Tania and Raghad Rowaida, “A Comparative Study of Various Image Filtering Techniques for Removing Various Noisy Pixels in Aerial Image”, International Journal of Signal Processing, Image Processing, and Pattern Recognition, Volume 9, No.3, pp.113-124, 2016.
[33] Ms. Shweta Gupta, Ms. Meenakshi, “A Review and Comprehensive Comparison of Image Denoising Techniques”, IEEE, page: 972-976, 2014.
[34] Kumar, Ashok & C. Trivedi, Harsh & Usha Nilkanthan, Mrs. (2015). Development of Salt-and-Pepper Denoising Techniques. 10.1109/ICECCT.2015.7226017.
[35] Arvind Kumar G., Dr. Ashok Kusagur, “Evaluation of Image Denoising Techniques A Performance Perspective”, International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), IEEE, pp. 1836-1839, 2016.
[36] M. C. Motwani, M. C. Gadiya, R. C. Motwani, Jr. Harris,” Survey of Image Denoising Techniques”, Proceedings of GSPX, pp. 27–30, 2004.
[37] A.K. Kanithi,” Study of Spatial and Transform Domain Filters for Efficient Noise Reduction”, Department of Electronics and Communication Engineering, National Institute of Technology, Rourkela, India, 2011.
[38] N.Bhoi,” Spatial-Domain and Transform-Domain Digital Image Filters”, Department of Electronics and Communication Engineering National Institute of Technology, Rourkela, India, 2009.
[39] I. M. El-Henawy, A. E. Amin, Kareem Ahmed, Hadeer Adel, “A Comparative Study On Image Deblurring Techniques”, International Journal of Advances in Computer Science and Technology (IJACST), Volume 3, No.12, pp. 01-08, 22nd December 2014.
[40] Dejee Singh, Mr. R. K. Sahu, “A Survey on Various Image Deblurring Techniques”, International Journal of Advanced Research in Computer and Communication Engineering, Volume 2, Issue 12, pp. 4736-4739, December 2013.
[41] Zohair Al-Ameen, Ghazali Sulong, and Md. Gapar Md. Johar, “A Comprehensive Study on Fast image Deblurring Techniques”, International Journal of Advanced Science and Technology, Volume 44, pp. 1-10, July 2012.
[42] M.Kalpana Devi, R.Ashwini, “An Analysis on Implementation of various Deblurring Techniques in Image Processing”, International Research Journal of Engineering and Technology (IRJET), Volume 03 Issue: 12, pp. 1049-1059, Dec 2016.
[43] Pooja Dhole and Nitin Chopde, “A Comparative Approach for Analysis of Image Restoration using Image Deblurring Techniques”, International Journal of Current Engineering and Technology, Volume 5, No.2, pp. 1046-1049, April 2015.
[44] Kamaldeep Joshi, Rajkumar Yadav, “PSNR and MSE Based Investigation of LSB”, International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), IEEE, pp. 280-285, 2016.
[45] M. Radhika Mani, V. Lalithya, P.Swetha Rekha, “An Innovative Approach for Pattern Based Image Steganography”, IEEE, presented at the Int Conf Signal Processing, Informatics, Communication, and Energy Systems, pp. 1-4, 2015.
[46] Kalpana Chaurasia and Mrs. Nidhi Sharma, “Performance Evaluation and Comparison of Different Noise, apply on PNG Image Format used in DE convolution Wiener filter (FFT) Algorithm”, Evolving Trends in Engineering and Technology, Volume 4, pp 8-14, 2015.
[47] https://in.mathworks.com/help/vision/ref/psnr.html
[48] https://en.wikipedia.org/wiki/Root-mean-square_deviation
[49] Anil Kumar Gupta, Dibya Jyoti Bora, Fayaz Ahmad Khan, “Multispectral Satellite Color Image Segmentation Using Fuzzy Based Innovative Approach”, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Volume 3, Issue1, pp. 968-975, January-February-2018.
[50] Gagan Madaan, “Various Approaches of Content Based Image Retrieval Process: A Review”, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Volume 3, Issue 1, pp. 711-716, January-February-2018.