In order to achieve high efficiency, automatic and accurate measurement, the paper takes the two-dimensional measurement of industrial glass under the experimental conditions. The main contents of this paper includes: Analyzing the structure and hardware performance parameters of the system, building a measuring platform including computer, Charge-coupled Device image sensor, lens, etc., using high-precision camera to take the image of glass, preprocessing of glass image data and acquiring edge information of glass. The system use second filtering method to filter the image and Canny operator to acquire the edge of the industry glass, transforming computer coordinate system into world coordinate system through coordinate transformation method, and finally calculate the two-dimensional size information of industrial glass. The system measures the two-dimensional length and width of polygonal glass, the experimental results show that the measurement method in this paper meet the accuracy requirements of general industrial measurement, and the detection system is feasible.
The extraction of Region of Interest (ROI) is an important information guarantee in the application of imaging matching guidance, which directly affects the acquisition probability and matching accuracy of the target. Image segmentation is an important method to extract the Region of Interest of the target. Based on image segmentation algorithm, histogram equalization and morphological filtering, this paper proposes an effective image processing method to extract the Region of Interest of the target. (1) A variety of image threshold segmentation methods are applied to the actual processing flow, and their segmentation performance is compared and analyzed. Some image segmentation methods are obtained, which are suitable for target region extraction in template image preparation and target potential region location in matching recognition. (2) Preliminary localization of visible remote sensing images is carried, using color information, to obtain local regions, then enhance the image using histogram equalization method, finally morphological filtering is used to remove the edge noise. (3) The Otsu method and Kittler minimum error method are processed in parallel, then the segmentation results are fused, and the evaluation indexes such as area constraint, similarity and contrast are filtered to obtain the target region .Tests have been done with visible image and infrared image in this paper. The result indicates that the effectiveness of the morphological filter is more obvious after histogram equalization for the original image. Besides, the Otsu method and Kittler minimum error method are processed in parallel, then the segmentation results are fused to get a more precise Region of Interest, thus ensuring the accuracy and timeliness of imaging matching guidance.
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