Manuscript Number : IJSRST52310623

Apple Disease Detection Using Deep Learning

Authors(6) :-K. R. Surendra, E. Anitha, B. Prathyusha, G. T. Tarun Reddy, B. N. Maheswar Reddy, B Pavan Kumar Naik

This paper proposes a technique for detecting and diagnosing diseases in apple fruits using image processing and deep learning methods. The proposed technique involves a series of steps, including input image acquisition, pre-processing, adaptive filtering with median filter, image enhancement, morphological analysis, fuzzy clustering, segmentation using k-means algorithm, feature extraction with Gray level co-occurrence matrix (GLCM), and classification with a deep convolutional neural network (CNN) classifier. The output of the proposed technique is the detection and classification of various diseases in apple fruits. The proposed technique is implemented using MATLAB 2018a Version and tested with several datasets. The results demonstrate that the proposed technique can effectively detect and diagnose diseases in apple fruits with high accuracy and can be used as a valuable tool in the agricultural industry.

Authors and Affiliations

K. R. Surendra
Assistant Professor, Department of Electronics and Communication Engineering, SV College of Engineering (SVCE), Tirupati, Andhra Pradesh, India
E. Anitha
Department of Electronics and Communication Engineering, SV College of Engineering (SVCE), Tirupati, Andhra Pradesh, India
B. Prathyusha
Department of Electronics and Communication Engineering, SV College of Engineering (SVCE), Tirupati, Andhra Pradesh, India
G. T. Tarun Reddy
Department of Electronics and Communication Engineering, SV College of Engineering (SVCE), Tirupati, Andhra Pradesh, India
B. N. Maheswar Reddy
Department of Electronics and Communication Engineering, SV College of Engineering (SVCE), Tirupati, Andhra Pradesh, India
B Pavan Kumar Naik
Department of Electronics and Communication Engineering, SV College of Engineering (SVCE), Tirupati, Andhra Pradesh, India

Deep learning Algorithm, CNN Classifier, GLCM, Image Segmentation, Apple Fruit

  1. Malathy, S., Karthiga, R. R., Swetha, K., & Preethi, G. “Disease detection in fruits using image processing”. In 2021 6th International Conference on Inventive Computation Technologies (ICICT) (pp. 747-752). IEEE,2021, January.
  2. Devi, P. K. “Image Segmentation K-Means Clustering Algorithm for Fruit Disease Detection Image Processing”.In 2020 4th International Conference on Electronics, Communication and Aerospace Technology(ICECA) (pp.861-865).IEEE,2020, November.
  3. Wang, H., Mou, Q., Yue, Y., & Zhao, H.” Research on detection technology of various Fruit disease spots based on mask R-CNN”. In 2020 IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 1083-1087). IEEE, 2020, October.
  4. Behera, S. K., Jena, L., Rath, A. K., & Sethy, P. K. “Disease classification and grading of oranges using machine learning and fuzzy logic”. In 2018 International Conference on Communication and Signal Processing (ICCSP) (pp. 0678-0682). IEEE, 2018, April.
  5. Zhao, J., & Qu, J.“A detection method for tomato Fruit common physiological diseases based on YOLOv2”. In 2019 10th international conference on Information Technology in Medicine and Education (ITME) (pp. 559-563). IEEE, 2019, August.
  6. Abirami, S., & Thilagavathi, M. “Classification of Fruit diseases using feed forward back propagation neural network”. In 2019 International Conference on Communication and Signal Processing (ICCSP) (pp. 0765-0768). IEEE, 2019, April.
  7. Nikitha, M., Sri, S. R., & Maheswari, B. U. “ Fruit recognition and grade of disease detection using inception v3 model”. In 2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 1040-1043). IEEE,2019, June.
  8. Dharmasiri, S. B. D. H., & Jayalal, S.” Passion Fruit Disease Detection using Image Processing”. In 2019 International Research Conference on Smart Computing and Systems Engineering (SCSE) (pp. 126-133). IEEE, 2019, March.

Publication Details

Published in : Volume 11 | Issue 1 | January-February 2024
Date of Publication : 2024-02-29
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 214-221
Manuscript Number : IJSRST52310623
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

K. R. Surendra, E. Anitha, B. Prathyusha, G. T. Tarun Reddy, B. N. Maheswar Reddy, B Pavan Kumar Naik, " Apple Disease Detection Using Deep Learning ", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 11, Issue 1, pp.214-221, January-February-2024.
Journal URL : https://ijsrst.com/IJSRST52310623
Citation Detection and Elimination     |      | | Malathy, S., Karthiga, R. R., Swetha, K., & Preethi, G. “Disease detection in fruits using image processing”. In 2021 6th International Conference on Inventive Computation Technologies (ICICT) (pp. 747-752). IEEE,2021, January.
  • Devi, P. K. “Image Segmentation K-Means Clustering Algorithm for Fruit Disease Detection Image Processing”.In 2020 4th International Conference on Electronics, Communication and Aerospace Technology(ICECA) (pp.861-865).IEEE,2020, November.
  • Wang, H., Mou, Q., Yue, Y., & Zhao, H.” Research on detection technology of various Fruit disease spots based on mask R-CNN”. In 2020 IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 1083-1087). IEEE, 2020, October.
  • Behera, S. K., Jena, L., Rath, A. K., & Sethy, P. K. “Disease classification and grading of oranges using machine learning and fuzzy logic”. In 2018 International Conference on Communication and Signal Processing (ICCSP) (pp. 0678-0682). IEEE, 2018, April.
  • Zhao, J., & Qu, J.“A detection method for tomato Fruit common physiological diseases based on YOLOv2”. In 2019 10th international conference on Information Technology in Medicine and Education (ITME) (pp. 559-563). IEEE, 2019, August.
  • Abirami, S., & Thilagavathi, M. “Classification of Fruit diseases using feed forward back propagation neural network”. In 2019 International Conference on Communication and Signal Processing (ICCSP) (pp. 0765-0768). IEEE, 2019, April.
  • Nikitha, M., Sri, S. R., & Maheswari, B. U. “ Fruit recognition and grade of disease detection using inception v3 model”. In 2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 1040-1043). IEEE,2019, June.
  • Dharmasiri, S. B. D. H., & Jayalal, S.” Passion Fruit Disease Detection using Image Processing”. In 2019 International Research Conference on Smart Computing and Systems Engineering (SCSE) (pp. 126-133). IEEE, 2019, March.
    • " target="_blank"> BibTeX     | Malathy, S., Karthiga, R. R., Swetha, K., & Preethi, G. “Disease detection in fruits using image processing”. In 2021 6th International Conference on Inventive Computation Technologies (ICICT) (pp. 747-752). IEEE,2021, January.
  • Devi, P. K. “Image Segmentation K-Means Clustering Algorithm for Fruit Disease Detection Image Processing”.In 2020 4th International Conference on Electronics, Communication and Aerospace Technology(ICECA) (pp.861-865).IEEE,2020, November.
  • Wang, H., Mou, Q., Yue, Y., & Zhao, H.” Research on detection technology of various Fruit disease spots based on mask R-CNN”. In 2020 IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 1083-1087). IEEE, 2020, October.
  • Behera, S. K., Jena, L., Rath, A. K., & Sethy, P. K. “Disease classification and grading of oranges using machine learning and fuzzy logic”. In 2018 International Conference on Communication and Signal Processing (ICCSP) (pp. 0678-0682). IEEE, 2018, April.
  • Zhao, J., & Qu, J.“A detection method for tomato Fruit common physiological diseases based on YOLOv2”. In 2019 10th international conference on Information Technology in Medicine and Education (ITME) (pp. 559-563). IEEE, 2019, August.
  • Abirami, S., & Thilagavathi, M. “Classification of Fruit diseases using feed forward back propagation neural network”. In 2019 International Conference on Communication and Signal Processing (ICCSP) (pp. 0765-0768). IEEE, 2019, April.
  • Nikitha, M., Sri, S. R., & Maheswari, B. U. “ Fruit recognition and grade of disease detection using inception v3 model”. In 2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 1040-1043). IEEE,2019, June.
  • Dharmasiri, S. B. D. H., & Jayalal, S.” Passion Fruit Disease Detection using Image Processing”. In 2019 International Research Conference on Smart Computing and Systems Engineering (SCSE) (pp. 126-133). IEEE, 2019, March.
    • " target="_blank">RIS     | Malathy, S., Karthiga, R. R., Swetha, K., & Preethi, G. “Disease detection in fruits using image processing”. In 2021 6th International Conference on Inventive Computation Technologies (ICICT) (pp. 747-752). IEEE,2021, January.
  • Devi, P. K. “Image Segmentation K-Means Clustering Algorithm for Fruit Disease Detection Image Processing”.In 2020 4th International Conference on Electronics, Communication and Aerospace Technology(ICECA) (pp.861-865).IEEE,2020, November.
  • Wang, H., Mou, Q., Yue, Y., & Zhao, H.” Research on detection technology of various Fruit disease spots based on mask R-CNN”. In 2020 IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 1083-1087). IEEE, 2020, October.
  • Behera, S. K., Jena, L., Rath, A. K., & Sethy, P. K. “Disease classification and grading of oranges using machine learning and fuzzy logic”. In 2018 International Conference on Communication and Signal Processing (ICCSP) (pp. 0678-0682). IEEE, 2018, April.
  • Zhao, J., & Qu, J.“A detection method for tomato Fruit common physiological diseases based on YOLOv2”. In 2019 10th international conference on Information Technology in Medicine and Education (ITME) (pp. 559-563). IEEE, 2019, August.
  • Abirami, S., & Thilagavathi, M. “Classification of Fruit diseases using feed forward back propagation neural network”. In 2019 International Conference on Communication and Signal Processing (ICCSP) (pp. 0765-0768). IEEE, 2019, April.
  • Nikitha, M., Sri, S. R., & Maheswari, B. U. “ Fruit recognition and grade of disease detection using inception v3 model”. In 2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 1040-1043). IEEE,2019, June.
  • Dharmasiri, S. B. D. H., & Jayalal, S.” Passion Fruit Disease Detection using Image Processing”. In 2019 International Research Conference on Smart Computing and Systems Engineering (SCSE) (pp. 126-133). IEEE, 2019, March.
    • " target="_blank">CSV

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