Abstract

At present, systems for the recognition (classification) of reflectors based on artificial neural networks are being actively developed to increase the speed of preparation of the ultrasonic testing protocol and reduce the influence of the human factor. For these systems to operate most efficiently, the reflector images must be processed in order to increase the signal-to-noise ratio of the image and its segmentation (clustering). One way of segmentation is to process the image with an adaptive anisotropic diffusion filter, which is used to process optical images. The effectiveness of using this texture filter for segmentation of reflector images reconstructed from echo signals measured with antenna arrays has been demonstrated in model experiments.

中文翻译：

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自适应各向异性扩散滤光片在超声无损检测中提高反射镜图像质量的应用

摘要

目前，正在积极开发基于人工神经网络的反射体识别（分类）系统，以加快超声波检测方案的制定速度，减少人为因素的影响。为了使这些系统最有效地运行，必须处理反射器图像以增加图像的信噪比及其分割（聚类）。一种分割方法是使用自适应各向异性扩散滤波器处理图像，该滤波器用于处理光学图像。模型实验证明了使用这种纹理滤波器对从用天线阵列测量的回波信号重建的反射器图像进行分割的有效性。