The Classification of Flower Features using Artificial Intelligence from Ganga Choti Bagh Azad Kashmir

Classification of Flower Features using Artificial Intelligence from Ganga Choti Bagh Azad Kashmir

https://doi.org/10.48185/jaai.v3i1.431

Authors

  • Sajid Ali Khan GREEN HILLS POSTGRADUATE COLLEGE RAWALAKOT POONCH AZAD KASHMIR PAKISTAN
  • Ishtiaq Afzal Government Postgraduate College Rawalakot Poonch Azad Kashmir Pakistan

Keywords:

AI, GLCM, Image Classification, Flower

Abstract

This research utilized surface and shading highlights for blossom grouping. Standard data set of blossoms have utilized for tests. The pre-handling like clamor expulsion and division for end of foundation are applied on input pictures. Surface and shading highlights are separated from the portioned pictures. Surface component is removed utilizing GLCM (Gray Level Co-event Matrix) technique and shading highlight is separated utilizing Color second. For arrangement, neural organization classifier is utilized. The general precision of the framework is 96.0%.

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References

Mukane, S. M., & Kendule, J. A. (2013). Flower classification using neural network based image processing. IOSR Journal of Electronics and Communication Engineering, 7(3), 80-85.

Tiay, T., Benyaphaichit, P., & Riyamongkol, P. (2014, March). Flower recognition system based on image processing. In 2014 Third ICT International Student Project Conference (ICT-ISPC) (99-102). IEEE.

Hong, S. W., & Choi, L. (2012, October). Automatic recognition of flowers through color and edge based contour detection. In 2012 3rd International conference on image processing theory, tools and applications (IPTA) (141-146). IEEE.

Guru, D. S., Sharath, Y. H., & Manjunath, S. (2010). Texture features and KNN in classification of flower images. IJCA, Special Issue on RTIPPR (1), 21-29.

Basavanna, M., & Gornale, S. S. (2015). Identification and Classification of Flowers Images using Colour models. International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), 1003-1007.

Angelova, A., Zhu, S., & Lin, Y. (2013, January). Image segmentation for large-scale subcategory flower recognition. In 2013 IEEE Workshop on Applications of Computer Vision (WACV) (39-45). IEEE.

Siraj, F., Ekhsan, H. M., & Zulkifli, A. N. (2014, October). Flower image classification modeling using neural network. In 2014 International Conference on Computer, Control, Informatics and Its Applications (IC3INA) (81-86). IEEE.

Guru, D. S., Kumar, Y. S., & Manjunath, S. (2011). Textural features in flower classification. Mathematical and Computer Modelling, 54(3-4), 1030-1036.

Seo, Y., & Shin, K. S. (2018, March). Image classification of fine-grained fashion image based on style using pre-trained convolutional neural network. In 2018 IEEE 3rd International Conference on Big Data Analysis (ICBDA) (387-390). IEEE.

Hnoohom, N., & Yuenyong, S. (2018, February). Thai fast food image classification using deep learning. In 2018 International ECTI northern section conference on electrical, electronics, computer and telecommunications engineering (ECTI-NCON) (116-119). IEEE.

Alsabahi, Y. A. L., Fan, L., & Feng, X. (2018, November). Image classification method in DR image based on transfer learning. In 2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA) (1-4). IEEE.

Published

2022-06-30

How to Cite

Khan, S. A., & Afzal, I. (2022). The Classification of Flower Features using Artificial Intelligence from Ganga Choti Bagh Azad Kashmir: Classification of Flower Features using Artificial Intelligence from Ganga Choti Bagh Azad Kashmir. Journal of Applied Artificial Intelligence, 3(1), 17–23. https://doi.org/10.48185/jaai.v3i1.431

Issue

Vol. 3 No. 1 (2022): 2022 (1)

Section

Articles
Copyright & Licensing

Copyright (c) 2022 Journal of Applied Artificial Intelligence

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