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Image Enhancement of Lemon Grasses Using Image Processing Techniques (Histogram Equalization)

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Data Science and Analytics (REDSET 2017)

Abstract

Lemon grass a type of medicinal plants has been part of human existence and has been applied in so many ways, like for healing, for drugs and for protection. In this paper, the conventional Histogram Equalization has been used to improve the images of the lemon grasses. MATLAB software was used to display the Histogram as well as the Histogram Equalization of the image of the lemon grasses. Image processing techniques to be used here is Histogram Equalization. The Histogram Equalization is considered, since it is one of the techniques in the enhancement of images and as such is being applied to the medicinal herb which in particular is the lemon grasses. The Histogram Equalization technique used may be seen as a conventional technique but the results obtained demonstrates its capability to improve the appearance of images by bringing out hidden details. The performance of the technique also shows that it is a better method in comparison to other types of Histogram Equalization methods.

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References

  1. Lili, N.A., Khalid, F., Borhan, N.M.: Classification of herbs plant diseases via hierarchical dynamic artificial neural network after image removal using kernel regression framework. Int. J. Comput. Sci. Eng. (IJCSE) 3, 15–20 (2011)

    Google Scholar 

  2. Nithiyanandhan, K., Mathpati, S.: Analysis of fractal dimension of medicinal leaves by using techniques of image processing. Int. Res. J. Eng. Technol. (IRJET) 3(8), 1531–1535 (2016)

    Google Scholar 

  3. Zhang, H., Tao, X.: Leaf image recognition based on wavelet and fractal dimension. J. Comput. Inf. Syst. 11(1), 141–148 (2015)

    Google Scholar 

  4. Rathod, A.N., Tanawal, B., Shah, V.: Image processing techniques for detection of leaf disease. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 3(11), 397–399 (2013)

    Google Scholar 

  5. Pande Ankita, V., Shandilya, V.K.: Digital image processing approach for fruit and flower leaf identification and recognition. Int. J. Eng. Comput. Sci. 2(4), 1280–1285 (2013). ISSN 23197242

    Google Scholar 

  6. Valliammai, N., Geethalakshmi, S.N.: A hybrid method for enhancement of plant leaf recognition. World Comput. Sci. Inf. Technol. J. 1(9), 370–375 (2011). ISSN 2221-0741

    Google Scholar 

  7. Gonzalez, R.C., Woods, R.E.: Digital Image Processing Using MATLAB. Pearson Education Inc., Upper Saddle River (2009)

    Google Scholar 

  8. Paragi, A.N.S.: Image contrast enhancement using histogram equalization. Accent J. Econ. Ecol. Eng. 2(3) (2017)

    Google Scholar 

  9. Zhu, Y., Huang, C.: An adaptive histogram equalization algorithm on the image gray level mapping. Phys. Procedia 25, 601–608 (2012)

    Article  Google Scholar 

  10. Kaura, T., Sidhub, R.K.: Second international symposium on computer vision and the internet (VisionNet 2015). Procedia Comput. Sci. 58, 470–477 (2015)

    Article  Google Scholar 

  11. Kaur, M., Kaur, J., Kaur, J.: Survey of contrast enhancement techniques based on histogram equalization. (IJACSA) Int. J. Adv. Comput. Sci. Appl., 2(7), 137–141 (2011)

    Google Scholar 

  12. Rathi, M.S., Karode, A.H., Suralkar, S.R.: Contrast enhancement and smoothing using histogram modification method for medical images. Int. J. Comput. Technol. Appl. 3(5), 1789–1798

    Google Scholar 

  13. Vij, K., Singh, Y.: Enhancement of images using histogram processing techniques. Int. J. Comp. Tech. Appl. 2(2), 309–313 (2011)

    Google Scholar 

  14. Sonker, D.: Comparison of histogram equalization techniques for image enhancement of grayscale images in natural and unnatural light. Int. J. Eng. Res. Dev. 8(9), 2476–2480 (2013)

    Google Scholar 

  15. Nimkar, S., Shrivastava, S., Varghese, S.: Contrast enhancement and brightness preservation using multi-decomposition histogram equalization. Sig. Image Process. Int. J. (SIPIJ) 4(3), 83–93 (2013)

    Google Scholar 

  16. Zhang, X.Y., Ge, L., Wang, T.F.: Entropy-based local histogram equalization for medical ultrasound image enhancement. In: 2nd International Conference on Bioinformatics and Biomedical Engineering, (2008)

    Google Scholar 

  17. Ziaei, A., Yeganeh, H., Faez K., Sargolzaei, S.: A novel approach for contrast enhancement in biomedical images based on histogram equalization. In: 2nd International Conference on Bioinformatics and Biomedical Engineering (2008)

    Google Scholar 

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Acknowledgement

We acknowledge the support and sponsorship provided by Covenant University through the Centre for Research, Innovation and Discovery (CUCRID).

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Correspondence to Sanjay Misra .

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Temiatse, O.S., Misra, S., Dhawale, C., Ahuja, R., Matthews, V. (2018). Image Enhancement of Lemon Grasses Using Image Processing Techniques (Histogram Equalization). In: Panda, B., Sharma, S., Roy, N. (eds) Data Science and Analytics. REDSET 2017. Communications in Computer and Information Science, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-10-8527-7_24

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  • DOI: https://doi.org/10.1007/978-981-10-8527-7_24

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  • Print ISBN: 978-981-10-8526-0

  • Online ISBN: 978-981-10-8527-7

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