Abstract
The detection of building wall surface defects is of great significance to eliminate potential safety hazards. In this paper, a research on building wall design defect image recognition based on partial differential equation is proposed. Collect the image data of building surface defects, sample and quantify the collected images, and preprocess the defect images such as digital threshold segmentation, filtering, and enhancement. Then, the improved partial differential equation is used to recognize the image as a whole. The second-order partial differential diffusion equation and the fourth-order partial differential equation are used to recognize the high-frequency and low-frequency bands of the image, respectively. The kernel principal component analysis algorithm is used to transfer the overall image input space to the high-dimensional feature space. The kernel function is used to calculate the inner product in different subband images of the high-dimensional feature space to reduce the dimension of the overall image. The processed coefficients are inversely transformed by nondownsampling contour wave to realize the overall image recognition and ensure that the edge information of the source image does not disappear. Experimental results show that compared with other algorithms, the proposed algorithm has better effect and better stability.
Highlights
In recent years, with the rapid development of construction engineering technology, people’s requirements for construction quality are becoming more and more strict
The results show that the interference radiation sources in the defect image under the condition of background cause great interference to the recognition of the defect area
There are deficiencies in the overall method of building surface crack defect recognition, so it is of great significance to study the problem of building surface defect recognition
Summary
With the rapid development of construction engineering technology, people’s requirements for construction quality are becoming more and more strict. In the engineering practice and the quality research of modern engineering materials, the most common quality problem of building structure is the defect of wall surface, and the damage of building wall always starts from the defect. Small defects will interfere with the safety of the building, while large defects will destroy the structural integrity, shorten the service life of the building, lead to safety accidents, endanger people’s life and property safety, and produce serious consequences [3, 4]. The number of pixels surrounded by the spline curve in the X-coordinate interval is calculated by using the formula Y max ðIÞ − Y min ðIÞ + 1. For the “concave” defect, at the “concave” of the defect, the ordinate values of the boundary feature points under the same X-coordinate value are arranged from small to large, and their values show the following law: continuous increment-jump increment-continuous increment-jump increment-continuous increment.
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