Deformed Two-Dimension Code Quick Recognition Algorithm Design and Implementation in Uncertain Environment

2015 ◽  
Author(s):  
Zhu Siyang
Keyword(s):  
Algorithm Design ◽  
Recognition Algorithm ◽  
Two Dimension ◽  
Uncertain Environment ◽  
Design And Implementation

Algorithm Design and Implementation of Dynamic Star Simulator

2013 ◽  
Vol 722 ◽  
pp. 187-193
Author(s):  
Xiao Fang Zhao ◽  
Guang Bin Liu ◽  
Chao Shan Liu
Keyword(s):  
Traditional Method ◽  
Algorithm Design ◽  
Star Tracker ◽  
Simulation Algorithm ◽  
Arc Length ◽  
Visual Axis ◽  
Star Image ◽  
Design And Implementation ◽  
Simulation Testing ◽  
Celestial Sphere

In order to realize the simulation testing and calibration of star tracker in the lab, a simulation algorithm for dynamic and celestial sphere star image was proposed. This algorithm could complete simulation of star image at any time and any visual axis point, also could realize in-orbit simulation according to a given track. A new method of space district dividing was also presented in order to improve the traditional method of space district dividing by ascension and declination, fully considered declination arc length gradually shortened with latitude increasing. It can remarkably enhance the updating frequency simulation star image.

Recognition Algorithm Design and Complex Analysis for Languages of S-Nets

2010 ◽  
Vol 10 (1) ◽  
pp. 106-112 ◽  
Author(s):  
Tingting Cui ◽  
Qingtian Zeng ◽  
Dongli Zhang
Keyword(s):  
Complex Analysis ◽  
Algorithm Design ◽  
Recognition Algorithm

Automated Design of Image Recognition Process for Picking System

2016 ◽  
Vol 10 (5) ◽  
pp. 737-752 ◽  
Author(s):  
Taiki Ogata ◽  
◽  
Kazuaki Tsujimoto ◽  
Taigo Yukisawa ◽  
Yanjiang Huang ◽  
...  
Keyword(s):  
Image Recognition ◽  
Optimization Problem ◽  
Algorithm Design ◽  
Optimization Method ◽  
Automated Design ◽  
Recognition Algorithm ◽  
Design System ◽  
Patterned Surfaces ◽  
Recognition Method ◽  
F Measure

In this study, we propose an automated design system for an image recognition algorithm applicable to picking work in general and actual factory environments. Considering that an image recognition algorithm design consists of frameworks for selecting a rough recognition method from any of the three basic procedures of pre-processing of contained images, feature-extraction, and discrimination, we formulate it as an optimization problem and propose a random multi-start optimization method by which to derive solutions. We have conducted four types of evaluation experiments for the following four combinations: large or small degrees of similarity in the shape of objects to be recognized and whether they have patterned surfaces. The evaluation experiments show that the proposed design system succeeds in selecting a framework that fits the features of the objects to be recognized and that the designed basic processes have an F measure of 0.9 or more.

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