2021Revista Gestão Inovação e TecnologiasOpen access

Gradient Based Edge Detection of Traffic Image using Second Derivative Method Compared with First Derivative Method

K. Srinivasulu

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Abstract

Aim: To detect traffic images using Gradient based edge detection by Second derivative method compared with First derivative method. Materials and materials: A second derivative method is used in this study. Canny algorithm is the edge detection technique used in traffic images. With the help of this traffic has been detected in the images.26 is the sample size taken with p-value 0.8 and has been used to improve detection rate of Gradient based in terms of accuracy and sensitivity using better skewness. Result: According to the results obtained the Second derivative method has Accuracy 88.6% and Sensitivity is 83.4% compared with the accuracy of First derivative method has accuracy 83.22% and also sensitivity is 78.5%. It appears to be Accuracy (0.134) and Sensitivity (0.286) of the second derivative method compared with the First derivative method. Conclusion: it appears to be that the detection rate is better using a Second derivative method compared with the First derivative method in terms of Accuracy and Sensitivity.

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What this paper is about

Aim: To detect traffic images using Gradient based edge detection by Second derivative method compared with First derivative method. Materials and materials: A second derivative method is used in this study. Canny algorithm is the edge detection technique used in traffic images. With the help of this traffic has been detected in the images.26 is the sample size taken with p-value 0.8 and has been used to improve detection rate of Gradient based in terms of accuracy and sensitivity using better skewness. Result: According to the results obtained the Second derivative method has Accuracy 88.6% and Sensitivity is 83.4% compared with the accuracy of First derivative method has accuracy 83.22% and also sensitivity is 78.5%. It appears to be Accuracy (0.134) and Sensitivity (0.286) of the second derivative method compared with the First derivative method. Conclusion: it appears to be that the detection rate is better using a Second derivative method compared with the First derivative method in terms of Accuracy and Sensitivity.

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Available abstract

Aim: To detect traffic images using Gradient based edge detection by Second derivative method compared with First derivative method. Materials and materials: A second derivative method is used in this study. Canny algorithm is the edge detection technique used in traffic images. With the help of this traffic has been detected in the images.26 is the sample size taken with p-value 0.8 and has been used to improve detection rate of Gradient based in terms of accuracy and sensitivity using better skewness. Result: According to the results obtained the Second derivative method has Accuracy 88.6% and Sensitivity is 83.4% compared with the accuracy of First derivative method has accuracy 83.22% and also sensitivity is 78.5%. It appears to be Accuracy (0.134) and Sensitivity (0.286) of the second derivative method compared with the First derivative method. Conclusion: it appears to be that the detection rate is better using a Second derivative method compared with the First derivative method in terms of Accuracy and Sensitivity.

Key concepts: Derivative (finance), Second derivative, Sensitivity (control systems), Skewness, Directional derivative, Enhanced Data Rates for GSM Evolution, Mathematics, Material derivative

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