A subpixel edge detection method based on an arctangent edge model

Sun, Qiucheng; Hou, Yuexian; Tan, Qing

doi:10.1016/j.ijleo.2016.03.058

Cited by 28 publications

(9 citation statements)

References 26 publications

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“…Many common methods are used to detect lines in images [ 15 , 16 , 17 , 18 , 19 ], The Hough transform is one of those methods. When facing the problem of detecting steel bar lines, its results may not be rational in many conditions, an even erroneous.…”

Section: Methodsmentioning

confidence: 99%

A High Precision Quality Inspection System for Steel Bars Based on Machine Vision

Zhang

et al. 2018

Sensors

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Steel bars play an important role in modern construction projects and their quality enormously affects the safety of buildings. It is urgent to detect whether steel bars meet the specifications or not. However, the existing manual detection methods are costly, slow and offer poor precision. In order to solve these problems, a high precision quality inspection system for steel bars based on machine vision is developed. We propose two algorithms: the sub-pixel boundary location method (SPBLM) and fast stitch method (FSM). A total of five sensors, including a CMOS, a level sensor, a proximity switch, a voltage sensor, and a current sensor have been used to detect the device conditions and capture image or video. The device could capture abundant and high-definition images and video taken by a uniform and stable smartphone at the construction site. Then data could be processed in real-time on a smartphone. Furthermore, the detection results, including steel bar diameter, spacing, and quantity would be given by a practical APP. The system has a rather high accuracy (as low as 0.04 mm (absolute error) and 0.002% (relative error) of calculating diameter and spacing; zero error in counting numbers of steel bars) when doing inspection tasks, and three parameters can be detected at the same time. None of these features are available in existing systems and the device and method can be widely used to steel bar quality inspection at the construction site.

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Section: Methodsmentioning

confidence: 99%

A High Precision Quality Inspection System for Steel Bars Based on Machine Vision

Zhang

et al. 2018

Sensors

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“…Rotation invariant Laplacian isotropic filter using second order derivatives was further refined by Marr and Hildereth as LoG function [1] and further improved by Canny [2]. Subpixel based edge detection method are discussed in [3] [6] [7]. Fast Image Edge Detection based on Faber Schauder Wavelet and Otsu threshold [4] and Neutrosophic Set structure using maximum norm entropy [5] are found to be the recent developments.…”

Section: Introductionmentioning

confidence: 99%

Cumulative Mean Intensity Differential Transition Algorithm for Edge Detection

2020

IJRTE

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Edge Detection plays a vital role in machine vision applications and thereby variety of edge detection algorithms being developed over time for both grey scale and colour images. In this paper, a new technique for edge detection called cumulative mean intensity differential transition algorithm (CuMIDT Algorithm) is proposed. This approach focuses on learning variations in the local pixel intensities and predicting the possible edge when the intensity deviation goes out of the stipulated window area. Ramps at the edge boundaries and zero crossing are addressed using differential transition model. Experimentation are done on standard FDDB dataset and real dataset. It is observed that the proposed approach gives better results when compared to the recently proposed novel edge detection algorithms.

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“…al., 2016 ), ant colony optimization ( Liu. & Fang, 2015 ), Cellular Automata ( Amrogowicz et al, 2016 ), Anisotropic Gaussian Kernels ( Zhang et al, 2017b ), and different edge detection approaches ( Sun et al, 2016 ;Zhang et al, 2017a ;Zareizadeh et. al., 2013 ) have also been proposed in the literature.…”

Section: Introductionmentioning

confidence: 99%

A new edge detection approach via neutrosophy based on maximum norm entropy

Sert

Avcı

2019

Expert Systems with Applications

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It is a quite important step to find object edges in applications such as object recognition, classification and segmentation. Therefore, the edge detection algorithm to be used directly influences the performance of these applications. In this study, a new edge detection method based on Neutrosophic Set (NS) structure via using maximum norm entropy (EDA-NMNE) is proposed. Many experts and intelligence systems, including the fuzzy system, do not satisfactorily succeed in resolving indeterminacies and deficiencies. However, in the NS approach, problems are solved by dividing them into True (T), False (F) and Indeterminacy (I) subsets. In addition, because the approach has a powerful algorithmic structure, NS's conditions with indeterminate and missing situations can be solved successfully. In this study, object edges can be found successfully with the proposed approach because edges of the object are considered as indeterminate. Thus, using the proposed EDA-NMNE, a strong intelligent expert system-based edge finding software was designed. In our study, 5 different object edge detection results were obtained by converting 5 different types of entropy into NS-based edge detection software. Thus, edge detection analysis has been performed by experimenting many types of entropy that have not been previously used for NS edge detection. The Metric Figure of Merit (FOM), Peak Signal-to-Noise Ratio (PSNR) analysis, mean square error (MSE) were used in this experimental study. Based on these results, highest FOM and PSNR values are obtained by using NORM entropy. In addition, the proposed edge detection approach were compared with Edge Detection Approach via Canny (EDA-C), Edge Detection Approach via Sobel (EDA-S), Edge Detection Approach via Variation-Adaptive Ant Colony Optimization (EDA-VAACO) and Edge Detection Approach via Active Contour without Edge (EDA-ACWE). FOM and PSNR tests have been used to evaluate the edge detection results obtained via 5 different methods. The findings demonstrated that the performance of the proposed edge detection approach is more successful compared to other methods.

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A subpixel edge detection method based on an arctangent edge model

Cited by 28 publications

References 26 publications

A High Precision Quality Inspection System for Steel Bars Based on Machine Vision

A High Precision Quality Inspection System for Steel Bars Based on Machine Vision

Cumulative Mean Intensity Differential Transition Algorithm for Edge Detection

A new edge detection approach via neutrosophy based on maximum norm entropy

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