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Abstract
In modern industries, high precision dimensional measurement plays a pivotal role in product inspection and sub-pixel edge detection is the core algorithm. Traditional interpolation and moment methods have achieved some success. However, those methods still have shortcomings. For example, the accuracy is still insufficient with the resolution limitation of the image sensor. Moreover, prediction results can be affected by image noise. With the recent success of deep learning technology, we propose a sub-pixel edge detection method based on convolution neural network (CNN) and bi-directional long short-term memory (LSTM). First, one-dimensional visual geometry group-16 (VGG-16) is employed to extract edge features. Then, a transformation operation is developed to generate sequence information. Lastly, bi-directional LSTM with fully-connected layers is introduced to output edge positions. Experimental results on our steel plate dataset demonstrate that our method achieves superior accuracy and anti-noise ability than traditional methods.
Highlights
A charge coupled device (CCD) is an important piece of digital imaging equipment
To further improve the accuracy of dimensional measurements with the limitation of image resolution, inspired by the analysis above, we propose a novel sub-pixel edge detection model based on convolution neural network (CNN) and bi-directional long short-term memory (LSTM), which simultaneously has high precision and anti-noise ability
We propose a sub-pixel edge detection method based on deep learning for high precision dimensional measurements
Summary
A charge coupled device (CCD) is an important piece of digital imaging equipment. With the rapid development of CCD sensors and computer hardware, high precision dimensional measurement systems based on machine vision have been gradually adopted by industries such as automobile manufacturing, iron and steel manufacturing, and electronic manufacturing [1]. There are examples of industries applying dimensional measurement for their products. We take the production line of steel plate in the Taiyuan iron and steel industry for research. Sheared steel plates are conveyed along with the roller; the aim of the task is to design a system for the measurement of length. Steel plate images are collected by two industrial-grade array CCD sensors and the length of the steel plate can be calculated by the sum of the field interval in the middle, and the steel plate’s length in the fields of two CCD sensors
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