基于改进Petri网和两级边缘检测算法的纺织品起球建模仿真与分析

P. Strbac, Miloš Pejanović, M. Reljić
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引用次数: 0

摘要

本文将改进的Petri网和两级边缘检测算法用于纺织品起球的建模、仿真、检测和分析。本文采用了两种模型。第一个模型是关于在纺织品上产生起球的图像。该模型使用并行性、同步性和模型标记的保存,以较低的抽象级别表示。在建模、仿真和分析的几次迭代之后,模型转换为特定的Python程序。这个程序生成几百张纺织品起球的图像。第二个模型是对生成的图像的准备进行建模、仿真和分析,以进入程序,该程序使用两级算法进行边缘检测并生成检测到的起球输出图像。图像准备包括比较具有纺织起球的图像和没有起球的图像的像素块(2x2, 4x4和8x8)。无论相应块之间的差异如何,都会对带有起球的图像进行修改。该图像是两级边缘检测算法的输入。本文给出了纺织起球图像的生成和起球检测图像的实例。由于比较块的大小导致的误差与所示的确切起球表面有关。图像的处理速度根据块的大小进行了比较分析。提出了利用升级Petri网和两级边缘检测算法进一步研究起球检测的指导方针。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling simulation and analysis of textile pilling by using Upgraded Petri nets and two-level edge detection algorithm
Upgraded Petri nets and a two-level edge detection algorithm for the modeling, simulation, detection, and analysis of textile pilling has used in this paper. There are two models in this paper. The first model is related to creating images with pilling on textiles. This model is represented at a low level of abstraction, using parallelism, synchronization, and preservation of model markup. After several iterations of the modeling, simulation, and analysis, the model transformed into a specific Python program. This program generates several hundred images of pilling on textiles. The second model refers to the modeling, simulation, and analysis of the preparation of generated images for entry into a program that uses a two-level algorithm for edge detection and generation of output images of detected pilling. An image preparation includes comparing pixel blocks (2x2, 4x4, and 8x8) of the image with textile pilling and the image without pilling. This image with pilling is modified regardless of the difference between the corresponding blocks. This image is an input to the two-level edge detection algorithm. The paper presents some examples of generated images of textile pilling and images with detected pilling. Errors due to the size of the comparison block about the exact pilling surface shown. The speed of image processing according to the size of the comparison blocks analyzed. Some guidelines represented for further research on pilling detection using Upgraded Petri nets and a two-level edge detection algorithm.
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