Sub-pixel Edge Detection Algorithm Research Articles

Visual positioning method of printed circuit boards based on spatial moments

With the increasing necessities for reliable printed circuit board (PCB) product, there has been a considerable demand for high-speed and high-precision vision positioning systems. To locate a PCB board with high accuracy and reliability with the positioning mark images, a new visual positioning method is introduced. Considering the limitations of Lyvers subpixel edge detection algorithm, such as the lower positioning accuracy, the larger errors at the neighborhood of the edge intersections, and the more computing time and the more cumbersome process of threshold selection, we propose an improved algorithm, in which coarse and accurate edge detection methods are adopted, and a new criterion is put forward to detect the edge points with Otsu method. Furthermore, a formula is developed to determine the edge intersections, whose subpixel coordinates are calculated with bilinear interpolation and conjugate gradient method. Additionally, the causes of principle errors are explored, and the error compensation formulas are derived at any angle edges of the three-level edge model. The last experimental results show that the improved algorithm has good versatility, and compared with Lyvers and Ghosal algorithm, the process of threshold selection is easier, the detected edges are thinner, and the positioning accuracy for all edge points is much higher.

In-line Critical Dimension Measurement System Development of LCD Pattern Proposed by Newly Developed Edge Detection Algorithm

As the essential techniques for the CD (Critical Dimension) measurement of the LCD pattern, there are various modules such as an optics design, auto-focus [1-4], and precise edge detection. Since the operation of image enhancement to improve the CD measurement repeatability, a ring type of the reflected lighting optics is devised. It has a simpler structure than the transmission light optics, but it delivers the same output. The edge detection is the most essential function of the CD measurements. The CD measurement is a vital inspection for LCDs [5-6] and semiconductors [7-8] to improve the production yield rate, there are numbers of techniques to measure the CD. So in this study, a new subpixel algorithm is developed through facet modeling, which complements the previous sub-pixel edge detection algorithm. Currently this CD measurement system is being used in LCD manufacturing systems for repeatability of less than 30 nm.

A sub-pixel edge detection algorithm based on Zernike moments

A novel hybrid technique of combining an improved morphological gradient operator and Zernike moments, named MGZ edge detection algorithm, is developed to meet the stringent requirements for measuring accuracies of charge coupled device metrology system. The mathematical morphological gradient and Zernike moment algorithm are discussed based on the pixels grey-scale and spatial structure information of the images. To improve the algorithm process, the image edge is oriented and extracted by using improved morphological gradient operator firstly; then, the calculation errors of the typical ideal step edge model are analysed and corrected by the proposed error compensation formula. The edge point is relocated with sub-pixel accuracy by means of Zernike moment operator based on the edge point vectors and the threshold value. Finally, the sub-pixel edge detecting of the image is attained. The extensive experimental results show that the measuring error of the edge point is compensated reliably and accurately, and the new algorithm has short operation time, more precise and stronger robustness to noise than the prior similar algorithms. Meanwhile, the proposed method can well meet the need of charge coupled device metrology system for sub-pixel edge detection.

Application of Least Square Algorithm for Ellipses Detection

It is a significant process to automatically extract ellipses or elliptic image features in highly precise vision detection, especially to achieve rapid as well as accurate detection in complex environment. Fortunately, this paper provides an approach to solve the problem. We firstly detect the edge of images by using sub-pixel edge detection algorithm, and then determine the elliptical shapes, and eliminate the non-ellipses. For the complicated context and taking into account the occlusion of ellipses, we integrate the robust Hough transforms and slip window into randomized algorithm based on least square approach with the purpose of having got the veracious ellipse parameters, which proves that the approach is available for images in stability and accuracy.

Improved Algorithm for Sub-Pixel Edge Detection Based on Zernike Moments

The principle of Zernike moments and the method of sub-pixel edge detection based on Zernike moments were introduced in this paper. With the consideration of the limitation of the sub-pixel edge detection algorithm by Ghosal, such as the lower location precision of the edge and the extracted wider edge than that of the original image, an improved algorithm was proposed. On the one hand, a mask of size nine multiply nine was calculated and could be applied for the edge detection. On the other hand, a new criterion for edge detection was put forward. Additionally, a series of experiments were designed and implemented. The experiment results show that accuracy of the improved algorithm is higher than that obtained from using other size templates and Ghosal algorithm.

Sub-pixel edge detection algorithm based on Gauss fitting

Concerning the low accuracy in localization and sensitivity to noise in traditional edge detection algorithms,a sub-pixel edge detection algorithm based on function curve fitting,Gauss fitting of gradient direction sub-pixel edge detection algorithm was proposed.This method firstly chosed a series of points near the edge,then got the grey level of these points,and then tried to get the gradient level of these points.Then Gauss curves were used to fit the gradient levels of these points.Finally the axis of the Gauss curves was got by fitting,and the position of axis would be the sub-pixel edge position.The experimental results show that this algorithm can localize the sub-pixel edge position accurately.The comparision with other two algorithms shows that the running time of this algorithm is shorter,and the efficiency is relatively higher.

Subpixel Edge Detection of Autofocus for Micro-Machine Vision System

Aiming at the subpixle edge detection of speckle in autofocus for micro-machine vision, a novel accurate subpixel edge detection algorithm was proposed. The image of the part to be inspected was binaried by simple threshold algorithm. The noise in image was eliminated by blob area threshold algorithm. The pixel level edge detection was done and the single-pixel width connected pixel level contour was acquired by binary mathematical morphological algorithm. The subpixel level edge detection was completed and the subpixel level contour was obtained by 9×9 pixel rectangular lens algorithm based on cubic spline interpolation. The example result indicate that calculation speed of the algorithm proposed herein is fast, anti-noise performance is high, inspection accuracy is high, and subpixel edge location accuracy can reach to μm level.

The Research of the Measures Algorithm of the Parameter of the Cutter

Edge detection is the most basic problem in the process of image processing. The precision of traditional edge detection algorithm is not very high, it unable to meet the high precision need of modern industrial test technology. In order to overcome the deficiency, this text proposed subpixel edge detection algorithm based on the function curve fitting-Gauss fitting of gradient direction sub-pixel edge detection algorithm. According to the gradient distribution of the image, this text use gauss curve fitting the edge in order to realize the sub-pixel location. This text compared this algorithm with sub-pixel edge detection based on the LOG operator and sub-pixel edge detection based on the quadratic, and draw that this algorithm not only have the short running time and high efficiency, but also has proved that the algorithm has rotation invariant through the experiment. It is that pattern recognition and picture measure the important pretreatment means in the course to follow the method at the border, contradiction at accuracy and speed that but follow the method and exist at the traditional border. To above-mentioned problems, this text proposes following algorithms at the border based on model, and then try to get the diameter of the cutter. The experiment shows this algorithm at the realization border that can be very good and follows, measure the comparison of the algorithm through two kinds of diameters, drawing the running time of least square method shorter, efficiency is relatively high.