Mobile image processing system based on the Raspberry Pi 4 platform

2021 ◽  
Vol 12 (1) ◽  
pp. 16-25
Author(s):  
Łukasz Chlastawa
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Processing Time ◽  
Processing System ◽  
Raspberry Pi ◽  
Mean Square ◽  
Fast Fourier Transform Algorithm ◽  
Image Processing System ◽  
Basic Assumptions ◽  
Spectral Transformations

The article presents an image processing system based on the Raspberry Pi (RPi) platform. At the beginning of the article, the basic assumptions and purpose of the system are discussed. The following section presents the structure and operation of the system. The window application managing the system and allowing to perform contextual and spectral transformations on images as well as the measurement of parameters such as image processing time and mean square error (MSE) was discussed. The transformations performed were based both on ready formulas contained in the OpenCV library and the author's implementations, including the function implementing the Fast Fourier Transform algorithm radix-2. Examples of transformations were presented along with their usefulness. In the end, the development potential of the created system is presented and its application in specific solutions is proposed.

Development of Kansei Design System Using Image Processing

2007 ◽  
Author(s):  
Masao Arakawa ◽  
Hiroyuki Kitajima ◽  
Masahiro Ishida ◽  
Tadaharu Manabe
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Processing System ◽  
Visual Design ◽  
Design System ◽  
Human Engineering ◽  
Competitive Power ◽  
Image Processing System ◽  
Design Database

It is often said that it might be very important to take Kansei, some kind of human sensuous inspiration, into account of design. And it becomes more and more important especially in the design of products whose functions are saturated and it becomes difficult to gain competitive power only by adding a new function. In those cases, it is difficult to gain competitive power by neither discounting its prices nor making efforts in human engineering sense of ease in handling. In such cases, visual design will be more important, so that visual designers become key of success in the product. However, Kansei design used to be based on questionnaires to the customers, and it is basically based on putting emphasis on the greatest common of them. But, in most of cases visual designers would like to show their feelings into design and lead majority to his or her sense. So that Kansei design database is often useless to them and it is sometimes obstacle for their creativity. In this paper, we will propose the Kansei design system which is based on image processing system and qualifying image by using Fourier transform and make up a new visual design by using those Fourier transform data. As an example, we have used the proposed system in design of doors. We have verified the results by inspiration test and brain test and showed a possibility of the proposed method.

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

Massive Image Treatment System Based on Cloud Computing Platform

2014 ◽  
Vol 687-691 ◽  
pp. 3733-3737
Author(s):  
Dan Wu ◽  
Ming Quan Zhou ◽  
Rong Fang Bie
Keyword(s):  
Image Processing ◽  
Cloud Computing ◽  
High Performance ◽  
Large Scale ◽  
Processing System ◽  
Virtual Space ◽  
Image Processing System ◽  
Computing Platform ◽  
Simulation Calculation ◽  
Computer Resources

Massive image processing technology requires high requirements of processor and memory, and it needs to adopt high performance of processor and the large capacity memory. While the single or single core processing and traditional memory can’t satisfy the need of image processing. This paper introduces the cloud computing function into the massive image processing system. Through the cloud computing function it expands the virtual space of the system, saves computer resources and improves the efficiency of image processing. The system processor uses multi-core DSP parallel processor, and develops visualization parameter setting window and output results using VC software settings. Through simulation calculation we get the image processing speed curve and the system image adaptive curve. It provides the technical reference for the design of large-scale image processing system.

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