scholarly journals Retraction Note: Simulation of coastal beach stability and coastal running based on embedded image system

2021 ◽  
Vol 14 (22) ◽  
Author(s):  
Ziyan Li
2012 ◽  
Vol 9 (1) ◽  
pp. 235-242
Author(s):  
Jia-Shing Sheu ◽  
Zi-Hong Li ◽  
Chien-Pin Huang ◽  
Chi-Shan Yu ◽  
Tsong-Yau Hwang

2014 ◽  
Vol 667 ◽  
pp. 196-200
Author(s):  
Jie Zhang ◽  
Zhi Jian Dai ◽  
Shu Ying Cheng ◽  
Pei Jie Lin

This article presents a new design and implementation of a robust and efficient embedded image system which can perform image acquisition, data saving and communication. The system hardware consists of processors of CPLD and ARM, an OV7620 digital camera, an ISSI SRAM and some peripheral interfaces. The key part of the software is the usage of analogous DMA storage and processing technology which makes the image system have a higher efficiency. A memory allocation algorithm is developed to maximize parallel data access and make the utmost use of ARM’s processing ability, thus improving the system performance. Furthermore, a simple practical binary image processing algorithm is developed to enhance the performance of image processing in this article. The experimental result shows that the proposed design approach for a low cost embedded image system can achieve high performance, robustness and efficiency.


2020 ◽  
Vol 64 (3) ◽  
pp. 30401-1-30401-14 ◽  
Author(s):  
Chih-Hsien Hsia ◽  
Ting-Yu Lin ◽  
Jen-Shiun Chiang

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.


Author(s):  
Xiaoping Huang ◽  
Fangyi Wen ◽  
Zhongxin Wei

In recent years, with the development of communication technology, embedded computing technology and sensor technology, it has become increasingly mature. Micro sensors with sensing, computing and communication capabilities have appeared in large numbers and developed rapidly, making wireless sensor networks widely used. People put forward higher requirements for the accuracy, reliability and flexibility of the image acquisition system. The image transmission system using analog technology not only has low image quality, but also has a serious waste of system resources, is not easy to form a complex network structure, and has poor functional scalability. In view of the actual needs of the current image acquisition and wireless transmission system, based on embedded technology, image acquisition, processing technology and network transmission technology, this paper proposes and designs a low-cost, high-reliability embedded image acquisition and wireless transmission system. Experimental tests show that this system has reasonable design, high video coding efficiency, good image continuity, stable operation, and basically realizes the display, storage and playback functions of the collected video data. Improve the transmission rate of the system and reduce the distortion caused by compression in terms of image compression. At the same time, it supports multiple image resolutions, frame rate options and multiple video formats, and the system’s transmission rate can adapt to the state of the network. This design fulfills the basic requirements of an embedded image acquisition system based on network technology, and provides a good foundation for the next development of a gigabit network-based image acquisition system.


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