Recognition of Topology Feature of Graphene by Image Processing Technique

2013 ◽  
Vol 756-759 ◽  
pp. 4133-4137
Author(s):  
Mao Fa Wang ◽  
Ji Lin Feng ◽  
Xiao Ping Zou ◽  
Xiao Li Li ◽  
Pan Li ◽  
...  

In order to extract characteristic values of graphene, a method based on a series of digital image processing algorithms was proposed in this paper. Using the method, we can automatically analyze topology structure and calculate amount of carbon atoms, and even calculate chiral vector indices (n, m) during in-situ TEM scanning of graphene. At last, we also write the correlative software with c++, which applying the digital image processing algorithms, and give out the processing result of several classic TEM image of graphene.

2012 ◽  
Vol 19 (5) ◽  
pp. 1168-1174
Author(s):  
Li-Zhou ZHANG ◽  
Xiao-Yu HOU ◽  
Yu-Ming ZHANG ◽  
Hong-Jun LI ◽  
Yi-Song CHENG ◽  
...  

2010 ◽  
Vol 18 (6) ◽  
pp. 1340-1344
Author(s):  
Li-Zhou ZHANG ◽  
Dian-Wu WANG ◽  
Yu-Ming ZHANG ◽  
Yi-Song CHENG ◽  
Hong-Jun LI ◽  
...  

2007 ◽  
Vol 121-123 ◽  
pp. 1351-1354
Author(s):  
Yu Sheng Chien ◽  
Che Hsin Lin ◽  
Fu Jen Kao ◽  
Cheng Wen Ko

This paper proposes a novel microfluidic system for cell/microparticle recognition and manipulation utilizing digital image processing technique (DIP) and optical tweezer under microfluidic configuration. Digital image processing technique is used to count and recognize the cell/particle samples and then sends a control signal to generate a laser pulse to manipulate the target cell/particle optically. The optical tweezer system is capable of catching, moving and switching the target cells at the downstream of the microchannel. The trapping force of the optical tweezer is also demonstrated utilizing Stocks-drag method and electroosmotic flow. The proposed system provides a simple but high-performance solution for microparticle manipulation in a microfluidic device.


2020 ◽  
Vol 8 (5) ◽  
pp. 3026-3035

Manual examination is not as accurate to examine crop growing stages because of the possibility of the human mistake and errors. While machine examination or automatic examination can easily examine crop growing stages and increase productivity because it provides fast and accurate examine result. This study provide a solution to finding the wheat crop growth stages, Once the growing stages are established, farmers can take suitable and measured steps to improve the production of wheat or other agricultural crops. For finding the growth stages of wheat digital image processing technique is used. RGB model, HSI model, mean value of green colour, hue and saturation images use for examining wheat crop.


Sign in / Sign up

Export Citation Format

Share Document