Texture Detection of Aluminum Foil Based on Top‐Hat Transformation and Connected Region Segmentation

Abstract

A new method of texture detection for aluminum foil based on digital image processing technology is proposed. Top-hat transformation and image segmentation technology based on the connected domain are used to change the method of determining texture fraction by using human experience. Compared with the brightness method, pit detection method, and EBSD technology, this method can complete quantitative detection efficiently, automatically, and accurately, and reduce the detection time and manpower. It eliminates the instability of manual detection and ensures the accuracy of detection. By this method, the error of test results can be controlled within 1.6%, which is much better than 7.3% of the brightness method and 4% of the pitting method. It provides more accurate test results for the production process control of aluminum foil.

Detection of the Deep-Sea Plankton Community in Marine Ecosystem with Underwater Robotic Platform

“…Firstly, 'grayscale invariance' is one of the prerequisites of the HS optical flow method, but in actual operation, the amount of grayscale change is often close to 0 but not equal to 0. Therefore, the threshold β 1 is set to handle this situation, as shown in Equation (24).…”

“…Secondly, when there is no plankton and the optical flow happens to be small, if the values of the optical flow are not the opposite but the sum still conforms to Equation (24), the threshold β 2 needs to be set to solve this situation, as shown in Equation (25).…”

“…The results are shown in Figure 7, where Figure 7a represents some original images of the video, including sediment clouds, plankton, and uneven backgrounds. Top-Hat transform [24] is used to detect the location of the plankton in the image as shown in Figure 7b, the weakness of this algorithm is that there are some missed cases. Figure 7c and Figure 7d show the detection results of the frame difference method [25] and the motion estimation and image matching method [26], respectively.…”

Industrial Image Enhancement Method Based on Cloud Edge Fusion

“…Combining with the results of image edge detection, the top hat transformation results can be obtained by opening and closing the industrial image. The top hat transformation [18][19][20] is divided into white top hat transformation and black top hat transformation, which are expressed as WTH and BTH, respectively. The basic idea of image enhancement is to enlarge the contrast between the bright and dark areas.…”