The edge detection which comes from the classical Sobel operator in the image is based on the horizontal gradient and vertical gradient direction. On the basis of the template from two directions the method which is to detect the edges of eight directions is discussed in this paper. The image edge detection based on multiple directions can improve the accuracy of edge detection. The numerical experimental results show that the proposed method can get the smooth, continuous, multiple directions edges, and can reduce the loss of the information. The method proposed in this paper is to detect the edge of the image, which will result in higher accuracy. Especially for more complex texture image, the effect of edge detection is more obvious, and the pixel width is closer to a single pixel width. It is an effective method for edge detection.

The rapid development of the Internet of Things (IoT) is accompanied by a large number of equipment deployment. When the equipment fails or reaches its service life, tons of e-waste will be generated. Therefore, there is an urgent need to find environmentally friendly and effective ways to recycle and treat e-waste. In this paper, a method of classification detection and resource utilization of waste electronic components based on the triboelectric nanogenerator (TENG) is proposed, which provides a novel idea for electronic waste treatment. We studied the output voltage characteristics of different kinds of TENG based on waste electronic components subject to different environmental loadings. The output characteristics of TENG are explored, reflecting the e-waste categories and processing environment. TENG is also connected with hundreds of light-emitting diodes (LEDs) through rectifier bridge circuit, and the output performance of TENG is characterized by the number and intensity of LEDs.

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In this paper, we make use of the integral method which is commonly used in partial differential equations to get the difference scheme on five points, and then construct an anisotropic diffusion model based on the partial differential equation. The numerical experimental results show the diffusion model can effectively magnify the image, and can keep the edge character and details of the image. It is proved that the numerical computational method proposed for solving the model is very effective.

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