Oil Palm Plantation Image Analysis Using Quantum Image Processing Approach

Abstract

This study focuses on image processing (image processing) in detecting the edges of palm trees from several collections of images/images with several variations of pixel resolution with a quantum image processing approach to produce an accurate analysis so that it can be used for future sustainable research. Quantum Hadamard Edge Detection (QHED) is used to detect the edges of an image where the number of qubits used affects CPU processing time. The number of qubits used in this study was 2, 4, 6, 8, 10, and 12 qubits, while the number of qubits more than 12 could not be tested due to the limited RAM of the devices in this study. The final result of the research proves that QHED can detect the edges of an image where the fastest processing time is on the use of 6 qubits while the best edge detection process results are in the use of 2 qubits. In addition, this study also compares QHED with Canny and Sobel where the comparison between Canny and Sobel's processing time is still faster but the quality of the processing results is still better than QHED.