Skip to main content

Effect of Different Filtering Techniques on Medical and Document Image

  • Conference paper
  • First Online:
Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019 (NUSYS 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 666))

Included in the following conference series:

Abstract

Image enhancement is very important stages used in image processing. A normal image enhancement process is using the filtering technique. Filtering helps the problems of the image display and can improvise the quality of the image. The problems that always happened in the image is illumination, noise and under-light images. In addition, these problems also caused a few troubles for image recognition for the daily life of certain people for their work. The objective of this study is to explore and compare a few starts of art filtering techniques based on the mathematical algorithm of the filters and then identifying the best method of the filters. There were a few methods that were selected in this project such as a high pass filter, low pass filter, high boost filter and others. All the selected filter experimented on the medical images and document images. The resulting images were evaluated using the Image Quality Assessments (IQA) which is a global contrast factor (GCF) and signal to noise ratio (SNR). Based on the numerical result, homomorphic low pas filter (HLF) provides a better performance among the other filters in terms of GCF (2.066) and SNR (8.907) value of the selected images.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 449.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 449.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Al-Rawi M, Qutaishat M, Arrar M (2007) An improved matched filter for blood vessel detection of digital retinal images. Comput Biol Med 37:262–267

    Article  Google Scholar 

  2. Thilagamani S, Shanthi N (2014) Gaussian and Gabor filter approach for object segmentation. J Comput Inf Sci Eng 14:1–7. https://doi.org/10.1115/1.4026458

    Article  Google Scholar 

  3. Chandel R, Gupta G (2013) Image filtering algorithms and techniques: a review. Int J Adv Res Comput Sci Softw Eng 3:198–202

    Google Scholar 

  4. Mustafa WA, Yazid H, Yaacob S (2015) Illumination correction of retinal images using superimpose low pass and Gaussian filtering. In: International conference on biomedical engineering (ICoBE), pp 1–4

    Google Scholar 

  5. Sehad A, Chibani, Y, Hedjam R, Cheriet M (2018) Gabor filter-based texture for ancient degraded document image binarization. https://doi.org/10.1007/s10044-018-0747-7

  6. Xu X, Liu B, Zhou F (2013) Hessian-based vessel enhancement combined with directional filter banks and vessel similarity. In: 2013 ICME international conference on complex medical engineering, CME 2013, pp 80–84. https://doi.org/10.1109/ICCME.2013.6548216

  7. Mustafa WA, Yazid H, Yaacob S (2014) A review : comparison between different type of filtering methods on the contrast variation retinal images. In: IEEE international conference on control system, computing and engineering, pp 542–546

    Google Scholar 

  8. Rajendran R, Panetta K (2016) A versatile edge preserving image enhancement approach for medical images using guided filter. In: IEEE international conference on systems, man and cybernetics, SMC 2016, pp 2341–2346

    Google Scholar 

  9. Li S, Kang X, Hu J (2013) Image fusion with guided filtering. IEEE Trans Image Process 22:2864–2875. https://doi.org/10.1109/TIP.2013.2244222

    Article  Google Scholar 

  10. Rajendran R, Rao SP, Agaian SS, Liss M (2016) A novel technique to enhance low resolution CT and magnetic resonance images. In: Simulation series

    Google Scholar 

  11. Shivakumarswamy GM, Aksha Patil V, Chethan TA, Prajwal BH, Hande SV (2016) Brain tumour detection using Image processing and sending tumour information over GSM. Int J Adv Res Comput Commun Eng 5:179–183. https://doi.org/10.17148/IJARCCE.2016.5543

    Article  Google Scholar 

  12. Mustafa WA, Yazid H, Yaacob S (2014) Illumination normalization of non-uniform images based on double mean filtering. In: IEEE international conference on control systems, computing and engineering, pp 366–371

    Google Scholar 

  13. Mustafa WA, Yazid H, Kader MMMA (2018) Luminosity correction using statistical features on retinal images. J Biomim Biomater Biomed Eng. 37:74–84. https://doi.org/10.4028/www.scientific.net/JBBBE.37.74

    Article  Google Scholar 

  14. Zhu S, Zeng B, Yan S (2012) Image super-resolution via low-pass filter based multi-scale image decomposition. In: Proceedings - IEEE international conference on multimedia and expo, pp 1045–1050. https://doi.org/10.1109/ICME.2012.29

  15. Liu M, Wang A (2014) Fully homomorphic encryption and its applications. Comput Sci Res Dev 51:2593–2603. https://doi.org/10.7544/issn1000-1239.2014.20131168

    Article  Google Scholar 

  16. Gangkofner UG, Pradhan PS, Holcomb DW (2008) Optimizing the high-pass filter addition technique for image fusion. Photogramm Eng Rem S 74:1107–1118. https://doi.org/10.14358/PERS.74.9.1107

    Article  Google Scholar 

  17. Alirezanejad M, Amirgholipour S, Safari V, Aslani S, Arab M (2014) Improving the performance of spatial domain image watermarking with high boost filter. Indian J Sci Technol 7:2133–2139

    Article  Google Scholar 

  18. Mustafa WA, Kader MMMA (2018) Contrast enhancement based on fusion method: a review. J Phys Conf Ser 1019:1–7. https://doi.org/10.1088/1742-6596/1019/1/012025

    Article  Google Scholar 

  19. Gu H, Lv W (2012) A modified homomorphic filter for image enhancement. In: Proceedings of the 2nd international conference on computer application and system modeling. https://doi.org/10.2991/iccasm.2012.45

  20. Mustafa WA, Khairunizam W, Yazid H, Ibrahim Z, Ab S, Razlan ZM (2018) Image correction based on homomorphic filtering approaches : a study. In: IEEE international conference on computational approach in smart systems design and applications (ICASSDA). IEEE, pp 1–5

    Google Scholar 

  21. Mustafa WA, Yazid H, Jaafar M, Zainal M, Abdul- AS, Mazlan N (2017) A review of image quality assessment (IQA): SNR, GCF, AD, NAE, PSNR, ME. J Adv Res Comput Appl 7:1–7

    Google Scholar 

  22. Mustafa WA, Yazid H (2016) Background correction using average filtering and gradient based thresholding. J Telecommun Electron Comput Eng 8:81–88

    Google Scholar 

  23. Mustafa WA, Yazid H (2016) Illumination and contrast correction strategy using bilateral filtering and binarization comparison. J Telecommun Electron Comput Eng 8:67–73

    Google Scholar 

  24. Kanafiah SNAM, Mashor MY, Mustafa WA, Mohamed Z (2018) A novel contrast enhancement technique based on combination of local and global statistical data on malaria images. J Biomim Biomater Biomed Eng 38:23–30. https://doi.org/10.4028/www.scientific.net/JBBBE.38.23

    Article  Google Scholar 

  25. Matkovic K, Neumann L, Neumann A, Psik T, Purgathofer W (2005) Global contrast factor - a new approach to image contrast. In: Computational aesthetics in graphics, visualization and imaging, pp 159–167

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme (FRGS/1/2018/SKK13/UNIMAP/02/1).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wan Azani Mustafa .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mustafa, W.A., Sam, S., Jamlos, M.A., Khairunizam, W. (2021). Effect of Different Filtering Techniques on Medical and Document Image. In: Md Zain, Z., et al. Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019 . NUSYS 2019. Lecture Notes in Electrical Engineering, vol 666. Springer, Singapore. https://doi.org/10.1007/978-981-15-5281-6_52

Download citation

Publish with us

Policies and ethics