Abstract
This paper proposes a simple Edges Extraction Method from complex digital Images (EEMI). The proposed EEMI uses a simple image processing technique to detect edges of objects and regions inside complex scenarios of images. It highlights objects’ edges by increasing their contrast levels and pixels’ intensities using special masks. EEMI mainly uses two simple masks one of which is used to detect vertical edges while the other one detects horizontal edges. Results have revealed that EEMI is a robust edge detector with inclined and complex background images. EEMI has been found simple and has simple complexity that helps reduce the computational time existent with other competitive methods. Results have confirmed that EEMI’s computation time could efficiently meet real-time requirements. EEMI has been compared to other competitive operators in terms of accuracy and computation time.
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
Lin W-C, Wang J-W (2018) Edge detection in medical images with quasi high-pass filter based on local statistics. Biomed Signal Process Control 39:294–302
Gupta D, Anand RS (2017) A hybrid edge-based segmentation approach for ultrasound medical images. Biomed Signal Process Control 31:116–126
Luo L, Tang Y, Lu Q, Chen X, Zhang P, Zou X (2018) A vision methodology for harvesting robot to detect cutting points on peduncles of double overlapping grape clusters in a vineyard. Comput Ind 99:130–139
Min C, Jiqiang S, Lyu MR (2002) A new approach for video text detection. In: Proceedings. International conference on image processing, vol 1, pp I-117–I-120
Du S, Ibrahim M, Shehata M, Badawy W (2013) Automatic License Plate Recognition (ALPR): a state-of-the-art review. IEEE Trans Circuits Syst Video Technol 23:311–325
Liu Z, Chen H, Blondel W, Shen Z, Liu S (2018) Image security based on iterative random phase encoding in expanded fractional Fourier transform domains. Opt Lasers Eng 105:1–5
Kmieć M, Glowacz A (2015) Object detection in security applications using dominant edge directions. Pattern Recogn Lett 52:72–79
Al-Ghaili AM, Mashohor S, Ramli AR, Ismail A (2013) Vertical-edge-based car-license-plate detection method. IEEE Trans Veh Technol 62:26–38
Bradley D, Roth G (2007) Adaptive thresholding using the integral image. J Graph Tools 12:13–21
Shafait F, Keysers D, Breuel TM (2008) Efficient implementation of local adaptive thresholding techniques using integral images. In: Document recognition and retrieval XV, p 681510
Sobel I (1990) An isotropic 3×3 gradient operator. In: Freeman H (ed) Machine vision for three-dimensional scenes. Academic Press, New York, pp 376–379
Al-Ghaili AM, Mashohor S, Ismail A, Ramli AR (2008) A new vertical edge detection algorithm and its application. In: 2008 international conference on computer engineering & systems, pp 204–209
Acknowledgements
This research is funded by UNIIG-J510050781; which is supported by Universiti Tenaga Nasional.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Al-Ghaili, A.M., Kasim, H., Othman, M., Hassan, Z. (2019). A Simple Edges Extraction Method from Complex Digital Images (EEMI). In: Piuri, V., Balas, V., Borah, S., Syed Ahmad, S. (eds) Intelligent and Interactive Computing. Lecture Notes in Networks and Systems, vol 67. Springer, Singapore. https://doi.org/10.1007/978-981-13-6031-2_16
Download citation
DOI: https://doi.org/10.1007/978-981-13-6031-2_16
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6030-5
Online ISBN: 978-981-13-6031-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)