TY - GEN
T1 - Logo recognition system
AU - Pornpanomchai, Chomtip
AU - Boonsripornchai, Passakorn
AU - Puttong, Pimchanok
AU - Rattananirundorn, Chonnipa
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/2/8
Y1 - 2016/2/8
N2 - The objective of this research is to develop computer software for recognizing a company logo. The system is called "Logo Recognition System or LRS". There are 2 parts of the LRS, namely: A client part and server part. The client part consists of common device, which is owned by the user, such as a mobile device, tablet and smart phone. On the client part, the LRS provides an easy graphic user interface for capturing a logo image. After that the device sends the logo image to the server part. The server part is a computer server, which does a process of recognizing with several algorithms and generates a result with a link of the logo's company website. The LRS consists of 4 components, namely: 1) Image Acquisition 2) Image Preprocessing 3) Image Recognition, and 4) Result Presentation. The system uses the python program to develop the logo recognition system on both client and server. The LRS can recognize the rotation image with any angle. The precision rate of the system is around 79.6 percent.
AB - The objective of this research is to develop computer software for recognizing a company logo. The system is called "Logo Recognition System or LRS". There are 2 parts of the LRS, namely: A client part and server part. The client part consists of common device, which is owned by the user, such as a mobile device, tablet and smart phone. On the client part, the LRS provides an easy graphic user interface for capturing a logo image. After that the device sends the logo image to the server part. The server part is a computer server, which does a process of recognizing with several algorithms and generates a result with a link of the logo's company website. The LRS consists of 4 components, namely: 1) Image Acquisition 2) Image Preprocessing 3) Image Recognition, and 4) Result Presentation. The system uses the python program to develop the logo recognition system on both client and server. The LRS can recognize the rotation image with any angle. The precision rate of the system is around 79.6 percent.
KW - Image processing
KW - Logo Recognition
KW - Pattern Recognition
UR - https://www.scopus.com/pages/publications/84964391065
U2 - 10.1109/ICSEC.2015.7401394
DO - 10.1109/ICSEC.2015.7401394
M3 - Conference contribution
AN - SCOPUS:84964391065
T3 - ICSEC 2015 - 19th International Computer Science and Engineering Conference: Hybrid Cloud Computing: A New Approach for Big Data Era
BT - ICSEC 2015 - 19th International Computer Science and Engineering Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th International Computer Science and Engineering Conference, ICSEC 2015
Y2 - 23 November 2015 through 26 November 2015
ER -