Abstract
When the computer recognizes the original color images and the collected images without changing the color information, it is a question to choose the appropriate color space for image recognition. In order to find out the best color space for image recognition, four color spaces were chosen to compare the similarity of the image between the original images and the collected images in different color spaces. In the premise of maintaining the image recognition accuracy, it can simplify the process of the image recognition by choosing the color space as the image pretreatment process.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Liu, H.-B., Shen, J., & Guo, S. (2010). Chapter 9. In S.-B. Zhang (Ed.), Digital image processing using visual C++. China: China Machine Press.
Zhang, Y., Liu, X., & Li, H. (2007). The precision of RGB color space convert to YCbCr color space. Journal of Southern Yangtze University (Natural Science Edition), 6(2), 200–202.
Xu, Y.-F. (2011). Chapter 4. In Color management principles and applications. Printing Industry Press.
Liu, H.-X. (2008). Chapter 3. Du, Y. F. (Ed.), Color science and technology. China: China Light Industry Press.
Wang, H.-M., Zhang, K., & Li, Y.-J. (2004). Computer Engineering and Application, 19, 42.
Walter, S., & Kenrick, M. (2014). Absolute C++ (5th ed.). China: Publishing House of Electronics.
Acknowledgments
The study is supported by the sub-topics ‘Technology Research on Painting Image Information Processing (10000200226)’ from the Ministry of Science and Technology of China’s project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this paper
Cite this paper
Tang, J., Yang, W. (2016). Comparing the Similarity of Image in Different Color Spaces. In: Ouyang, Y., Xu, M., Yang, L., Ouyang, Y. (eds) Advanced Graphic Communications, Packaging Technology and Materials. Lecture Notes in Electrical Engineering, vol 369. Springer, Singapore. https://doi.org/10.1007/978-981-10-0072-0_36
Download citation
DOI: https://doi.org/10.1007/978-981-10-0072-0_36
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0070-6
Online ISBN: 978-981-10-0072-0
eBook Packages: EngineeringEngineering (R0)