Article
Quantum Science & Technology
Wenjie Liu, Lu Wang
Summary: This paper proposes a novel QSED algorithm based on eight-direction Sobel operator, which reduces the loss of edge information and concurrently calculates gradient values in eight directions. The concrete quantum circuits are designed, and the complexity of the algorithm is lower than other existing classical or quantum algorithms. Simulation experiments demonstrate that the proposed algorithm can detect more edge information, especially diagonal edges, compared to two- and four-direction QSED algorithms.
QUANTUM INFORMATION PROCESSING
(2022)
Article
Quantum Science & Technology
R. Chetia, S. M. B. Boruah, P. P. Sahu
Summary: This study introduces a quantum improved Sobel edge detection algorithm with non-maximum suppression and double threshold techniques, providing more edge information. By analyzing the quantum circuit, number of edge pixels, simulation results, and circuit complexity, it is found that this algorithm achieves significant improvements in edge information and circuit complexity. The algorithm is compared with classical and existing quantum edge detection algorithms, showing superior performance.
QUANTUM INFORMATION PROCESSING
(2021)
Article
Quantum Science & Technology
Lu Wang, Zhiliang Deng, Wenjie Liu
Summary: This paper presents an improved quantum segmentation algorithm for NEQR images, which can segment complex grayscale images into clear ternary images using fewer qubits and can be scaled as needed. Experiments demonstrate the effectiveness of this algorithm in image segmentation.
QUANTUM INFORMATION PROCESSING
(2022)
Article
Computer Science, Information Systems
Panchi Li
Summary: Edge detection is a fundamental problem in digital image processing, and the Canny edge detector is widely used for this task. This paper presents a study on the implementation of the Canny edge detector using quantum computing. The proposed method introduces new operators and quantum circuits to accelerate the classical counterpart and improve the efficiency. The complexity analysis reveals that the quantum Canny edge detector shows exponential speedup compared to its classical counterpart. The implementation of the quantum Canny edge detector is the main contribution of this paper, which is validated through simulations on a classical computer.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Quantum Science & Technology
Yiming Yu, Jie Gao, Xiaoyi Mu, Shumei Wang
Summary: In this paper, a novel scheme for quantum image watermarking based on NEQR is proposed, which can embed a 2(n-1) x 2(n-1) binary watermark image into a 2(n) x 2(n) grayscale carrier image. The embedded image is highly consistent with the carrier image after restoration by only embedding the least significant bits of the diagonal details of the carrier image with the watermark information. The proposed watermarking method is confirmed to be invisible and robust through simulation techniques.
QUANTUM INFORMATION PROCESSING
(2023)
Article
Computer Science, Theory & Methods
Ruiping Wang, Liangcai Zeng, Shiqian Wu, Kelvin K. L. Wong
Summary: This paper proposes an illumination-robust feature detection method, utilizing an adaptive threshold FAST and image preprocessing techniques, which significantly improves the repeatability rate and number of features. The method demonstrates significant advantages in terms of repeatability rate, number of repeated features, and detection stability evaluation indices.
Article
Astronomy & Astrophysics
Lu Wang, Wenjie Liu
Summary: In this paper, a quantum segmentation algorithm based on local adaptive threshold for NEQR image is proposed, which utilizes quantum mechanism to compute local thresholds for all pixels in a gray-scale image and quickly segment the image into a binary image. Several quantum circuit units are designed, and a complete quantum circuit is constructed with fewer qubits and quantum gates. Experimental results demonstrate the feasibility of our algorithm in the noisy intermediate-scale quantum (NISQ) era.
MODERN PHYSICS LETTERS A
(2022)
Article
Multidisciplinary Sciences
Rajib Chetia, Partha Pratim Sahu
Summary: The COVID-19 outbreak requires urgent global attention in terms of public health, and the use of rapid testing, vaccination, and isolation is crucial in breaking the transmission chain. Lung computed tomography (CT) plays a vital role in accurately detecting COVID-19. This study proposes an improved edge extraction algorithm that can accurately detect the clinical edges of infected lungs present in the early stages of COVID-19 patients, aiding in COVID-19 analysis.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Quantum Science & Technology
Suzhen Yuan, Wenhao Zhao, Shengwei Gao, Shuyin Xia, Bo Hang, Hong Qu
Summary: This paper presents a quantum image segmentation algorithm that utilizes quantum parallelism to provide exponential speedup compared to existing implementations, while reducing the number of auxiliary qubits.
QUANTUM INFORMATION PROCESSING
(2022)
Article
Optics
Vladimir Maksimovic, Mile Petrovic, Dragan Savic, Branimir Jaksic, Petar Spalevic
Summary: This paper introduces a novel approach to edge detection based on image complexity criteria and the use of adaptive algorithms and machine learning principles to estimate edge detection thresholds. The results indicate that image complexity significantly impacts edge detection, with the Roberts operator showing good performance for images with low to medium detail and the Canny operator being the best solution for images with high detail. The use of grid search-based method shows improvement in edge detection, particularly with the Canny operator, while random search method offers a more efficient optimization of parameters for estimating threshold values considering computational time.
Article
Physics, Multidisciplinary
Tao Li, Pengpeng Zhao, Yadong Zhou, Yidai Zhang
Summary: Line detection is a fundamental technique in image processing that extracts required information and reduces data volume. It serves as the basis for image segmentation and plays a crucial role in the process. This paper presents a quantum algorithm for line detection based on a line detection mask for novel enhanced quantum representation (NEQR). A quantum circuit and detailed module are designed for line detection in different directions. Simulation results on a classical computer demonstrate the feasibility of the proposed quantum method, which exhibits improved computational complexity compared to similar edge detection algorithms.
Article
Engineering, Electrical & Electronic
Yunhao Cui, Yi An, Wei Sun, Huosheng Hu, Xueguan Song
Summary: The proposed multiscale adaptive edge detector for images constructs multiscale pyramid images and calculates gradient maps and standard deviation maps to accurately distinguish edges from background. This edge detector adaptively identifies candidate edges and fuses them based on a novel voting mechanism, resulting in an accurate binarized edge map. Experimental results show that the proposed edge detector achieves good performance, benefiting measurement applications.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Computer Science, Artificial Intelligence
Ahmed Husham Al-Badri, Nor Azman Ismail, Khamael Al-Dulaimi, Ghalib Ahmed Salman, Md Sah Hj Salam
Summary: This study proposes a new model called Ensemble-Region Convolutional Neural Networks (E-RCNN) for weed detection. The model improves recognition capability by using three CNN extractor networks to extract more efficient features. Additionally, it introduces Adaptive Non-Maximum Suppression (ANMS) to overcome the limitations of conventional Non-Maximum Suppression (NMS) in detecting overlapping and occluded objects. Experimental results demonstrate that the proposed model outperforms traditional approaches in terms of detection rate.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Luis O. Lopez, Francisco Orts, Gloria Ortega, Vicente Gonzalez-Ruiz, Ester M. Garzon
Summary: In this paper, a fault-tolerant quantum dual-threshold algorithm is proposed for image segmentation. The algorithm reduces the number of T-gates to improve fault-tolerance and noise tolerance. Additionally, two comparator circuits are implemented to optimize the T-count and T-depth metrics for better performance.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Information Systems
Sanjay Chakraborty, Soharab Hossain Shaikh, Amlan Chakrabarti, Ranjan Ghosh
Summary: In this paper, a quantum image edge extraction technique is developed using the classical Robinson operator and a novel enhanced quantum representation. The proposed scheme implements Robinson masks and convolution operations with quantum shifted image sets, while utilizing quantum parallel computation and a threshold-based black box for edge point classification. The design and simulation analysis of the algorithm is conducted, and the results are compared with state-of-the-art image edge extraction algorithms in terms of PSNR, MSE, and execution time.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
