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Linear Discrimination Analysis Using Image Processing Optimization

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The Effect of Information Technology on Business and Marketing Intelligence Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1056))

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Abstract

When we talk about Machinery Vision and Deep Learning, we often talk about algorithms. In fact, mathematical models with computer knowledge are the basis of how we deal with graphical data to process the Image and make decision. Machine learning can play an important role in determining agricultural plant type in order to optimize the harvesting steps in an automated way. How to process and introduce the products to the market often requires detailed information about the stages of planting and harvesting. In addition, by using this method, sophisticated research can be designed in plant genetics and effect of environmental variables on the end product. The ultimate goal of this work is to use Linear Discrimination Analysis for the Image Processing and classification of harvested wheat grain which are belonged to different types of grain namely Rosa, Kama and Canadian. The above discovery has proved with the statistics to have with more than 94% of accuracy.

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Author information

Authors and Affiliations

  1. Faculty of Management, Canadian University Dubai, Dubai, UAE

    Raed A. Said

  2. Department of Computer Engineering, College of Engineering, Mutah University, Mu’tah, Jordan

    Nidal A. Al-Dmour

  3. College of Engineering and Information Technology, University of Science and Technology of Fujairah, Fujairah, UAE

    Liaqat Ali & Mohammed Salahat

  4. School of Business, Skyline University College, Sharjah, UAE

    Haitham M. Alzoubi

  5. Department of Marketing, School of Business, The University of Jordan, Amman, Jordan

    Muhammad Alshurideh

  6. Department of Management, College of Business, University of Sharjah, Sharjah, UAE

    Muhammad Alshurideh

Authors
  1. Raed A. Said
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  2. Nidal A. Al-Dmour
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  3. Liaqat Ali
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  4. Haitham M. Alzoubi
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  5. Muhammad Alshurideh
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  6. Mohammed Salahat
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Corresponding author

Correspondence to Haitham M. Alzoubi .

Editor information

Editors and Affiliations

  1. Dept of Mngmnt, Cllg of Busness Admin, University of Sharjah, Sharjah, United Arab Emirates

    Muhammad Alshurideh

  2. Department of Business Administration, Faculty of Economics and Administrative Sciences, Hashemite University, Zarqa, Jordan

    Barween Hikmat Al Kurdi

  3. Management Information Systems Department, School of Business, University of Jordan, Aqaba, Jordan

    Ra’ed Masa’deh

  4. Skyline University College, Sharjah, United Arab Emirates

    Haitham M. Alzoubi

  5. Research Institute of Sciences and Engineering, University of Sharjah, Sharjah, United Arab Emirates

    Said Salloum

Appendix [Python Code with Outputs]

Appendix [Python Code with Outputs]

The figure shows four lines of Python codes to import a dataset.
An image depicts a set of Python codes with outputs. This includes the class, range index with 210 entries, 8 data columns. The code uses 13.2 kilobytes of memory.

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Said, R.A., Al-Dmour, N.A., Ali, L., Alzoubi, H.M., Alshurideh, M., Salahat, M. (2023). Linear Discrimination Analysis Using Image Processing Optimization. In: Alshurideh, M., Al Kurdi , B.H., Masa’deh, R., Alzoubi , H.M., Salloum, S. (eds) The Effect of Information Technology on Business and Marketing Intelligence Systems. Studies in Computational Intelligence, vol 1056. Springer, Cham. https://doi.org/10.1007/978-3-031-12382-5_137

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