Fruit Disease Detection and Identification Using Image Processing

  • Dr Praveen Reddy Assistant Professor with Guru Nanak Dev Engineering College, Bidar, Karnataka, India

Abstract

This paper presents fruits disease detection using image processing technique. When diseases affect fruits there is significant decrease in the production of fruits due to which farmers suffer in selling their yield. This problem motivated to develop the new techniques to detect and diagnose the  diseases affecting fruits. To increase production and quality, it is necessary to control such harmful  diseases at the earlier stage. In our country most farmers are illiterate. So they cannot get correct information about fruits diseases. It requires an agricultural officer. But it is difficult for  an agricultural officer to reach at every farmer. In mentioned system digital image processing is fast and accurate technique for detection of diseases in fruits.


How to cite this article:
Reddy P, Heena, Tahreem F et al. Fruit Disease Recognition and Identification using Image Processing. J Adv Res Image Proc Appl 2020; 3(2): 17-21

Author Biography

Dr Praveen Reddy, Assistant Professor with Guru Nanak Dev Engineering College, Bidar, Karnataka, India

reddysirlogin@gmail.com,

References

[1] H. Al-Hiary et.al., “Fast and Accurate Detection and Classification of Plant Diseases”,
International Journal of Computer Applications (0975 – 8887)Volume 17– No.1, In the year March 2011

[2] Wenjiang Huang et.al., “New Optimized Spectral Indices for Identifying and Monitoring Winter Wheat Diseases”, IEEE journal of selected topics in applied earth observation and remote sensing,Vol. 7, No. 6, In the year June 2014

[3] Monica Jhuria, Ashwani Kumar, and Rushikesh Borse, “ The Image Processing For Smart Farming: Detection Of Disease And Fruit Grading”, Proceedings of the year 2013 IEEE Second International Conference on the Image Information Processing (ICIIP-2013)

[4] Zulkifli Bin Husin et.al. “Feasibility Study on Plant Chili Disease Detection Using Image Processing Techniques”, In the year 2012 Third International Conference on Intelligent Systems Modelling and Simulation.


[5] Mrunalini R. Badnakhe, Prashant R. Deshmukh, “Infected Leaf Analysis and Comparison by Otsu Threshold and k- Means Clustering”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 3, In the year March 2012.

[6] Chunxia Zhang, Xiuqing Wang, Xudong Li, “Design of Monitoring and Control Plant Disease System Based on DSP&FPGA”,In the year 2010 Second International Conference on Networks Security, Wireless Communications and Trusted Computing.

[7]. Devrim Unay and Bernard Gosselin, 2004."A Quality Grading Approach For 'Jonagold' Apples" Proceedings of SPS (IEEE Benelux Signal Processing Symposium)
[8]. Jayme Garcia Arnal Barbedo,2013." Digital image processing techniques for detecting, quantifying and classifying plant diseases" BarbedoSpringerPlus, 2:660
[9]. V. Leemans and M. F. Destain,2004." A real-time grading method of apples based on features extracted from

defects " Journal of Food Engineering 61 83–89, 2003 Elsevier
[10]. Manisha A. Bhange and Prof. H. A. Hingoliwala, 2015" A Review of Image Processing for Pomegranate Disease Detection". International Journal of Computer Science and Information Technologies, Vol. 6 (1) , 92-94
[11].Tejal Deshpande, SharmilaSengupta and K.S. Raghuvanshi, 2014"Grading & Identification of Disease in Pomegranate Leaf and Fruit". International Journal of Computer Science and Information Technologies, Vol. 5 (3), 4638-4645
[12].Suvarnakanakaraddi, prashantiliger, akshaygaonkar, minalalagoudar and abhinav prakash,2014."Analysis And Grading Of Pathogenic Disease Of Chilli Fruit Using Image Processing "Proceedings of International Conference on Advances in Engineering & Technology, ISBN: 978-93- 84209-06-3
Published
2020-12-03
How to Cite
REDDY, Dr Praveen. Fruit Disease Detection and Identification Using Image Processing. Journal of Advanced Research in Image Processing and Applications, [S.l.], v. 3, n. 2, p. 17-21, dec. 2020. Available at: <http://thejournalshouse.com/index.php/image-pocessing-applications/article/view/321>. Date accessed: 22 dec. 2024.