Comparing edge-detection algorithm performance under degrading signal-to-noise ratio conditions

2001 ◽  
Author(s):  
Kelce S. Wilson
Keyword(s):  
Edge Detection ◽  
Signal To Noise Ratio ◽  
Detection Algorithm ◽  
Signal To Noise ◽  
Algorithm Performance ◽  
Edge Detection Algorithm ◽  
Noise Ratio

Fiducial visibility on planar images during motion-synchronized tomotherapy treatments

2022 ◽  
Author(s):  
William Ferris ◽  
Larry Albert DeWerd ◽  
Wesley S Culberson
Keyword(s):  
Management System ◽  
Signal To Noise Ratio ◽  
Detection Algorithm ◽  
Position Error ◽  
Signal To Noise ◽  
Motion Management ◽  
Future Studies ◽  
Planar Images ◽  
Noise Ratio

Abstract Objective: Synchrony® is a motion management system on the Radixact® that uses planar kV radiographs to locate the target during treatment. The purpose of this work is to quantify the visibility of fiducials on these radiographs. Approach: A custom acrylic slab was machined to hold 8 gold fiducials of various lengths, diameters, and orientations with respect to imaging axis. The slab was placed on the couch at the imaging isocenter and planar radiographs were acquired perpendicular to the custom slab with varying thicknesses of acrylic on each side. Fiducial signal to noise ratio (SNR) and detected fiducial position error in millimeters were quantified. Main Results: The minimum output protocol (100 kVp, 0.8 mAs) was sufficient to detect all fiducials on both Radixact configurations when the thickness of the phantom was 20 cm. However, no fiducials for any protocol were detected when the phantom was 50 cm thick. The algorithm accurately detected fiducials on the image when the SNR was larger than 4. The MV beam was observed to cause RFI artifacts on the kV images and to decrease SNR by an average of 10%. Significance: This work provides the first data on fiducial visibility on kV radiographs from Radixact Synchrony treatments. The Synchrony fiducial detection algorithm was determined to be very accurate when sufficient SNR is achieved. However, a higher output protocol may need to be added for use with larger patients. This work provided groundwork for investigating visibility of fiducial-free solid targets in future studies and provided a direct comparison of fiducial visibility on the two Radixact configurations, which will allow for intercomparison of results between configurations.

scholarly journals Digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection

2021 ◽  
Vol 18 (5) ◽  
pp. 6771-6789
Author(s):  
Hongyan Xu ◽  
Keyword(s):  
Edge Detection ◽  
Digital Media ◽  
Copyright Protection ◽  
Detection Rate ◽  
Signal To Noise Ratio ◽  
Edge Computing ◽  
Absolute Difference ◽  
Watermark Image ◽  
Signal To Noise ◽  
Noise Ratio

<abstract> <p>With the rapid development of computer technology and network communication technology, copyright protection caused by widely spread digital media has become the focus of attention in various fields. For digital media watermarking technology research emerge in endlessly, but the results are not ideal. In order to better realize the copyright identification and protection, based on the embedded intelligent edge computing detection technology, this paper studies the zero watermark copyright protection algorithm of digital media. Firstly, this paper designs an embedded intelligent edge detection module based on Sobel operator, including image line buffer module, convolution calculation module and threshold processing module. Then, based on the embedded intelligent edge detection module, the Arnold transform of image scrambling technology is used to preprocess the watermark, and finally a zero watermark copyright protection algorithm is constructed. At the same time, the robustness of the proposed algorithm is tested. The image is subjected to different proportion of clipping and scaling attacks, different types of noise, sharpening and blur attacks, and the detection rate and signal-to-noise ratio of each algorithm are calculated respectively. The performance of the watermark image processed by this algorithm is evaluated subjectively and objectively. Experimental data show that the detection rate of our algorithm is the highest, which is 0.89. In scaling attack, the performance of our algorithm is slightly lower than that of Fourier transform domain algorithm, but it is better than the other two algorithms. The Signal to Noise Ratio of the algorithm is 36.854% in P6 multiplicative noise attack, 39.638% in P8 sharpening edge attack and 41.285% in fuzzy attack. This shows that the algorithm is robust to conventional attacks. The subjective evaluation of 33% and 39% of the images is 5 and 4. The mean values of signal to noise ratio, peak signal to noise ratio, mean square error and mean absolute difference are 20.56, 25.13, 37.03 and 27.64, respectively. This shows that the watermark image processed by this algorithm has high quality. Therefore, the digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection is more robust, and its watermark invisibility is also very superior, which is worth promoting.</p> </abstract>

scholarly journals Performance Analysis of Target Depth Classification Algorithm Based on Sea Experiment Data

2019 ◽  
Vol 2019 ◽  
pp. 1-18
Author(s):  
Anbang Zhao ◽  
Xuejie Bi ◽  
Nansong Li ◽  
Minghui Zhang ◽  
Shengchun Piao
Keyword(s):  
Velocity Profile ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Algorithm Performance ◽  
Sound Velocity Profile ◽  
Depth Classification ◽  
Noise Ratio ◽  
Target Depth ◽  
Negative Gradient ◽  
The Ideal

Cross-spectrum signals can be calculated by the pressure signals. The sign distribution of cross-spectrum active component can be effectively used for target depth classification algorithm. The algorithm is applicable for depth classification of targets where frequencies can only excite the first two normal modes. The corresponding research results are mainly based on the theoretical study. There are few researches on the algorithm performance based on experiment results. To overcome this research lack, based on the effective depth model, the effects on various receiving depth, source frequency, and received signal-to-noise ratio on the algorithm performance have been studied in this paper. The influence of sound velocity profile parameters (negative gradient, thermocline intensity, thermocline thickness, and up-boundary depth) on the algorithm performance has also been researched. According to the simulation results, proper adjustment of the receiving depths can effectively improve the algorithm performance. The source frequency primarily affects the position of the ideal receiving depth which can be appropriately adjusted according to the depth classification requirements of the real sea environment. The algorithm performance improves gradually with the increase of signal-to-noise ratio. Moreover, the algorithm can also be applied under the conditions of negative gradient and thermocline. The comprehensive sound velocity profile parameters have a large impact on the depth classification performance of the algorithm. Even in the case of strong negative gradient or strong thermocline, the robustness of the algorithm is still high. The feasibility of our presented method has been verified by sea experiment. The practical application value of the ideal receiving depth has been researched and validated. The factors affecting the algorithm performance including line spectrum continuity and received signal-to-noise ratio have also been analyzed in our simulation and real sea experiments.

scholarly journals A Direct Current Measurement Method Based on Terbium Gallium Garnet Crystal and a Double Correlation Detection Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2997
Author(s):  
Shen ◽  
Chen ◽  
Yu ◽  
Ge ◽  
Han ◽  
...  
Keyword(s):  
Direct Current ◽  
Measurement Method ◽  
Signal To Noise Ratio ◽  
Detection Algorithm ◽  
Current Measurement ◽  
Garnet Crystal ◽  
Signal To Noise ◽  
Control Measurement ◽  
Noise Ratio ◽  
Direct Current Measurement

When applying an optical current transformer (OCT) to direct current measurement, output signals exhibit a low signal-to-noise ratio and signal-to-noise band overlap. Sinusoidal wave modulation is used to solve this problem. A double correlation detection algorithm is used to extract the direct current (DC) signal, remove white noise and improve the signal-to-noise ratio. Our sensing unit uses a terbium gallium garnet crystal in order to increase the output signal-to-noise ratio and measurement sensitivity. Measurement errors of single correlation and double correlation detection algorithms are compared, and experimental results showed that this measurement method can control measurement error to about 0.3%, thus verifying its feasibility.

scholarly journals Modifikasi Ant Colony Optimization Berdasarkan Gradient Untuk Deteksi Tepi Citra

2015 ◽  
Vol 6 (3) ◽  
Author(s):  
Febri Liantoni ◽  
Nanik Suciati ◽  
Chastine Fatichah
Keyword(s):  
Edge Detection ◽  
Ant Colony Optimization ◽  
Signal To Noise Ratio ◽  
Ant Colony ◽  
Test Results ◽  
Signal To Noise ◽  
Average Value ◽  
Image Edge ◽  
Noise Ratio ◽  
Better Than

Abstract. Ant Colony Optimization (ACO) is an optimization algorithm which can be used for image edge detection. In traditional ACO, the initial ant are randomly distributed. This condition can cause an imbalance ants distribution. Based on this problem, a modified ant distribution in ACO is proposed to optimize the deployment of ant based gradient. Gradient value is used to determine the placement of the ants. Ants are not distributed randomly, but are placed in the highest gradient. This method is expected to be used to optimize the path discovery. Based on the test results, the use of the proposed ACO modification can obtain an average value of the Peak Signal to Noise Ratio (PSNR) of 12.724. Meanwhile, the use of the traditional ACO can obtain an average value of PSNR of 12.268. These results indicate that the ACO modification is capable of generating output image better than traditional ACO in which ants are initially distributed randomly.Keywords: Ant Colony Optimization, gradient, Edge Detection, Peak Signal to Noise Ratio Abstrak. Ant Colony Optimization (ACO) merupakan algoritma optimasi, yang dapat digunakan untuk deteksi tepi pada citra Pada ACO tradisional, semut awal disebarkan secara acak. Kondisi ini dapat menyebabkan ketidakseimbangan distribusi semut. Berdasarkan permasalahan tersebut, modifikasi distribusi semut pada ACO diusulkan untuk mengoptimalkan penempatan semut berdasarkan gradient. Nilai gradient digunakan untuk menentukan penempatan semut. Semut tidak disebar secara acak akan tetapi ditempatkan di gradient tertinggi. Cara ini diharapkan dapat digunakan untuk optimasi penemuan jalur. Berdasarkan hasil uji coba, dengan menggunakan ACO modifikasi yang diusulkan dapat diperoleh nilai rata-rata Peak Signal to Noise Ratio (PSNR) 12,724. Sedangkan, menggunakan ACO tradisional diperoleh nilai rata-rata PSNR 12,268. Hasil ini menunjukkan bahwa ACO modifikasi mampu menghasilkan citra keluaran yang lebih baik dibandingkan ACO tradisional yang sebaran semut awalnya dilakukan secara acak.Kata Kunci: Ant Colony Optimization, gradient, deteksi tepi, Peak Signal to Noise Ratio

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