Evaluation of canny and sobel operator for logo edge detection

Kutty, Suhaili Beeran; Saaidin, Shuria; Yunus, Puteri Nor Ashikin Megat; Hassan, Suhana Abu

doi:10.1109/istmet.2014.6936497

Cited by 16 publications

(5 citation statements)

References 1 publication

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“…We calculated the activation edge direction for each activation edge based on MATLAB's image processing algorithm for calculating directional gradient with the Sobel operator option 13 . Compared to other image processing algorithms, the Sobel operator is simple (an advantage for developing real‐time software) and can detect both edges and orientations of shapes 14 . It can however be sensitive to noise.…”

Section: Methodsmentioning

confidence: 99%

“…13 Compared to other image processing algorithms, the Sobel operator is simple (an advantage for developing real-time software) and can detect both edges and orientations of shapes. 14 It can however be sensitive to noise. The activation edge direction is the mean of the gradients calculated by the Sobel algorithm.…”

Section: Activation Edge Direction and Wavefront Directionmentioning

confidence: 99%

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Evaluation of RETRO‐Mapping for electrophysiological features including direction of plane activity during atrial fibrillation using multipolar catheters in humans

Smith

Coyle

Dhutia

et al. 2023

Cardiovasc electrophysiol

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Introduction: A quantifiable, automated standard of analyzing heart rhythm has long eluded cardiologists due, in part, to the limitations in technology and the ability to analyze large electrogram datasets. In this proof-of-concept study, we propose new measures to quantify plane activity in atrial fibrillation (AF) using our Representation of Electrical Tracking of Origin (RETRO)-Mapping software. Methods: We recorded 30 s segments of electrograms at the lower posterior wall of the left atrium using a 20-pole double loop catheter (AFocusII). The data were analyzed with the custom RETRO-Mapping algorithm in MATLAB. Thirty second segments were analyzed for number of activation edges, conduction velocity (CV), cycle length (CL), activation edge direction, and wavefront direction. These features were compared across 34 613 plane edges in three types of AF: persistent AF treated with amiodarone (11 906 wavefronts), persistent AF without amiodarone (14 959 wavefronts), and paroxysmal AF (7748 wavefronts). Change in activation edge direction between subsequent frames and change in overall wavefront direction between subsequent wavefronts were analyzed.Results: All activation edge directions were represented across the lower posterior wall. The median change in activation edge direction followed a linear pattern for all three types of AF with R 2 = 0.932 for persistent AF treated without amiodarone, R 2 = 0.942 for paroxysmal AF, and R 2 = 0.958 for persistent AF treated with amiodarone. All medians and the standard deviation error bars remained below 45°(suggesting all activation edges were traveling within a 90°s ector, a criterion for plane activity). The directions of approximately half of all wavefronts (56.1% for persistent without amiodarone, 51.8% for paroxysmal, 48.8% for persistent with amiodarone) were predictive of the directions of the subsequent wavefront.

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Section: Methodsmentioning

confidence: 99%

Section: Activation Edge Direction and Wavefront Directionmentioning

confidence: 99%

Evaluation of RETRO‐Mapping for electrophysiological features including direction of plane activity during atrial fibrillation using multipolar catheters in humans

Smith

Coyle

Dhutia

et al. 2023

Cardiovasc electrophysiol

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“…The Canny operator is a multi-level edge detection algorithm based on Grayscale. Kutty et al 26 used Canny operator and Sobel operator to detect logo edges respectively, and compared the detection effects of the two operators, the results of which showed that both methods can be used as auxiliary methods for logo detection. The Sobel operator is a common edge detection operator based on first-order derivatives.…”

Section: Related Workmentioning

confidence: 99%

Automatic tracking and intelligent observation of tidal bore propagation velocity based on UAV and computer vision

Zhang,

Zhan,

Ding

et al. 2024

Measurement and Control

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The rapidly developed Unmanned Aerial Vehicles (UAV) and artificial intelligence technology has prompted the real-time and accurate observation measurements of tidal bore, the basis of which is tidal bore propagation velocity. In this article, we construct a tidal observation system framework based on UAV and computer vision in order to obtain the tidal bore propagating velocity datasets. Firstly, we focus on the identification of tidal headlines based on the Sobel edge detection, the improved Otsu image segmentation algorithm and the edge connection algorithm with an accuracy of 91%. And then, the detected tidal headlines could be used to control the flight parameters of UAV in order to stably track tidal bore on the specified route with the deviation range below 0.5, and finally to acquire the tidal bore propagation velocity datasets. Comparing with the propagation velocity of the tidal line measured on site, the error of the results is maintained within 0.1 m/s, which demonstrates the effectiveness of our proposed observation method.

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“…It has diverse applications, such as object detection, image segmentation, and 3D reconstruction. We use the Sobel operator (Kutty et al, 2014) to extract significant edges from two original underwater images and their enhanced versions. As depicted in Figure 15B, our method produces clearer and more complete edge structures for prominent targets in the enhanced underwater images, indicating that our method performs well in underwater image edge extraction.…”

Section: Edge Extractionmentioning

confidence: 99%

RGB/Event signal fusion framework for multi-degraded underwater image enhancement

Bi,

Wang,

Guo

et al. 2024

Front. Mar. Sci.

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Underwater images often suffer from various degradations, such as color distortion, reduced visibility, and uneven illumination, caused by light absorption, scattering, and artificial lighting. However, most existing methods have focused on addressing singular or dual degradation aspects, lacking a comprehensive solution to underwater image degradation. This limitation hinders the application of vision technology in underwater scenarios. In this paper, we propose a framework for enhancing the quality of multi-degraded underwater images. This framework is distinctive in its ability to concurrently address color degradation, hazy blur, and non-uniform illumination by fusing RGB and Event signals. Specifically, an adaptive underwater color compensation algorithm is first proposed, informed by an analysis of the color degradation characteristics prevalent in underwater images. This compensation algorithm is subsequently integrated with a white balance algorithm to achieve color correction. Then, a dehazing method is developed, leveraging the fusion of sharpened images and gamma-corrected images to restore blurry details in RGB images and event reconstruction images. Finally, an illumination map is extracted from the RGB image, and a multi-scale fusion strategy is employed to merge the illumination map with the event reconstruction image, effectively enhancing the details in dark and bright areas. The proposed method successfully restores color fidelity, enhances image contrast and sharpness, and simultaneously preserves details of the original scene. Extensive experiments on the public dataset DAVIS-NUIUIED and our dataset DAVIS-MDUIED demonstrate that the proposed method outperforms state-of-the-art methods in enhancing multi-degraded underwater images.

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Evaluation of canny and sobel operator for logo edge detection

Cited by 16 publications

References 1 publication

Evaluation of RETRO‐Mapping for electrophysiological features including direction of plane activity during atrial fibrillation using multipolar catheters in humans

Evaluation of RETRO‐Mapping for electrophysiological features including direction of plane activity during atrial fibrillation using multipolar catheters in humans

Automatic tracking and intelligent observation of tidal bore propagation velocity based on UAV and computer vision

RGB/Event signal fusion framework for multi-degraded underwater image enhancement

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