Abstract
Microscopy images are acquired by capturing the microscopic view of blood sample under a microscope using a camera. The image quality is not that reliable further making bacteria segmentation a challenging task. Guided image filter (GIF) is reliable for contrast enhancement and noise reduction. Otsu thresholding (OT) has been a suitable algorithm for image segmentation. This paper proposes a combinative approach of aforesaid methods for segmentation of bacterial cells in microscopy images. The image quality assessment (IQA) of the enhanced image is evaluated using parameters like standard deviation (SD) and enhancement measure estimation (EME). This combinative approach produces better segmentation results, and the same is proved by IQA.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zielinski B, Oleksiak AS, Rymarczyk D, Piekarczyk A (2020) Deep learning approach to describing and classifying fungi microscopic images. PLoS ONE 1–21
Nizar A, Yigit A, Isik Z, Alpkocak A (2019) Identification of leukemia subtypes from microscopic images using convolutional neural network. Diagnostics 9(3):1–11
Jobson DJ, Rahman Z, Woodell GA (2001) Spatial aspect of color and scientific implications of retinex image processing. Visual Inf Process Int Soc Opt Photonics 4388:117–128
Rahman ZU, Jobson D, Woodell J, Woodell GA (2004) Retinex processing for automatic image enhancement. J Electron Imaging 13(1):100–110
Barnard K, Funt B (1997) Analysis and improvement of multi-scale retinex in color and imaging. Soc Imaging Sci Technol 1997(1):221–226
He K, Sun J, Tang X (2010) Guided image filtering. In: Proceedings of European conference on computer vision. Berlin, Heidelberg, pp 1–14
Win KY, Choomchuay S (2017) Automated segmentation of cell nuclei in cytology pleural fluid images using OTSU thresholding. In: Proceedings of International conference on digital arts, media and technology (ICDAMT). Chiang Mai, Thailand, pp 14–18
Oliver N, Morse B, Barret W (2011) A recursive Otsu thresholding method for scanned document binarization. In: Proceedings of IEEE workshop on applications of computer vision (WACV). Kona, HI, USA, pp 307–314
Awasthi N, Katare P, Gorthi SS, Yalavarthy PK (2020) Guided filter based image enhancement for focal error compensation in low cost automated histopathology microscopic system. J Biophotonics 13(11):1–23
Sharma A, Bhateja V, Sinha AK (2015) Synthesis of flash and no-flash image pairs using guided image filtering. In: Proceedings of 2nd International conference on signal processing and integrated networks (SPIN). Noida, India, pp 768–773
Gupta A, Tripathi A, Bhateja V (2013) Despeckling of SAR images in contourlet domain using a new adaptive thresholding. In: Proceedings of 3rd IEEE international advance computing conference (IACC). Ghaziabad, India, pp 1257–1261
Taquee A, Bhateja V, Shankar A, Srivastava A (2018) Combination of wavelets and hard thresholding for analysis of cough signals. In: Proceedings of second world conference on smart trends in systems, security and sustainability (WorldS4). London, UK, pp 266–270
Raj A, Srivastava A, Bhateja V (2011) Computer aided detection of brain tumor in magnetic resonance images. Int J Eng Technol 3(5):523–533
Bhateja V, Nigam M, Bhadauria AS, Arya A, Zhang EY (2019) Human visual system based optimized mathematical morphology approach for enhancement of brain MR images. J Ambient Intell Humanized Comput 1–9
Krishan A, Bhateja V, Sahu A (2014) Medical image fusion using combination of PCA and wavelet analysis. In: Proceedings of International conference on advances in computing, communications and informatics (ICACCI). Delhi, India, pp 986–991
The bacterial image dataset (DIBaS) is available online at: http://misztal.edu.pl/software/databases/dibas/. Last visited on 10 Dec 2020
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Yadav, A., Bhateja, V., Singh, D., Chauhan, B.K. (2022). Segmentation of Microscopy Images Using Guided Filter and Otsu Thresholding. In: Chowdary, P.S.R., Anguera, J., Satapathy, S.C., Bhateja, V. (eds) Evolution in Signal Processing and Telecommunication Networks. Lecture Notes in Electrical Engineering, vol 839. Springer, Singapore. https://doi.org/10.1007/978-981-16-8554-5_23
Download citation
DOI: https://doi.org/10.1007/978-981-16-8554-5_23
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-8553-8
Online ISBN: 978-981-16-8554-5
eBook Packages: EngineeringEngineering (R0)