Identification of Image Edge Using Quantum Canny Edge Detection Algorithm
DOI:
https://doi.org/10.5614/itbj.ict.res.appl.2019.13.2.4Keywords:
Canny, edge, edge detection, image, quantum, qubitAbstract
Identification of image edges using edge detection is done to obtain images that are sharp and clear. The selection of the edge detection algorithm will affect the result. Canny operators have an advantage compared to other edge detection operators because of their ability to detect not only strong edges but also weak edges. Until now, Canny edge detection has been done using classical computing where data are expressed in bits, 0 or 1. This paper proposes the identification of image edges using a quantum Canny edge detection algorithm, where data are expressed in the form of quantum bits (qubits). Besides 0 or 1, a value can also be 0 and 1 simultaneously so there will be many more possible values that can be obtained. There are three stages in the proposed method, namely the input image stage, the preprocessing stage, and the quantum edge detection stage. Visually, the results show that quantum Canny edge detection can detect more edges compared to classic Canny edge detection, with an average increase of 4.05%.Downloads
References
Rashmi, Kumar, M., & Saxena, R., Algorithm and Technique on Various Edge Detection: A Survey, Signal & Image Processing: An International Journal (SIPIJ), 4(3), pp. 65-75, 2013.
Jadwa, S.K., Canny Edge Detection Method for Medical Image, International Journal of Scientific Engineering and Applied Science (IJSEAS), 2(8), pp. 54-59, 2016.
Sundani, D., Mutiara, A.B., Juarna, A. & Agushinta, D., Edge Detection Algorithm for Color Image Based on Principle of Quantum Superposition, Journal of Theoretical and Applied Information Technology (JATIT), 76(2), pp. 152-159, 2015.
Reddy, D.N., Mohan, A.R. & Bhat, S., Canny Edge Detection using Verilog, International Journal of Engineering Sciences & Technology, 3(6), pp. 256-260, 2014.
Gupta, Y.K., A Novel Approach with Various Existing Edge Detection Techniques for Medical Imaging Modalities, Journal of Advanced Computing and Communication Technologies, 5(3), pp. 67-71, 2017.
Sulaeman, D., Nugroho, A.S., & Galinium, M., Iris Segmentation using Gradient Magnitude and Fourier Descriptor for Multimodal Biometric Authentication System, J. ICT Res. Appl., 10(3), pp. 209-227, 2016.
