IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Color Invariant Representation and Applications

Color Invariant Representation and Applications
View Sample PDF
Author(s): Abdelhameed Ibrahim (Mansoura University, Egypt), Takahiko Horiuchi (Chiba University, Japan), Shoji Tominaga (Chiba University, Japan)and Aboul Ella Hassanien (Cairo University, Egypt)
Copyright: 2017
Pages: 21
Source title: Handbook of Research on Machine Learning Innovations and Trends
Source Author(s)/Editor(s): Aboul Ella Hassanien (Cairo University, Egypt)and Tarek Gaber (Suez Canal University, Egypt)
DOI: 10.4018/978-1-5225-2229-4.ch046

Purchase

View Color Invariant Representation and Applications on the publisher's website for pricing and purchasing information.

Abstract

Illumination factors such as shading, shadow, and highlight observed from object surfaces affect the appearance and analysis of natural color images. Invariant representations to these factors were presented in several ways. Most of these methods used the standard dichromatic reflection model that assumed inhomogeneous dielectric material. The standard model cannot describe metallic objects. This chapter introduces an illumination-invariant representation that is derived from the standard dichromatic reflection model for inhomogeneous dielectric and the extended dichromatic reflection model for homogeneous metal. The illumination color is estimated from two inhomogeneous surfaces to recover the surface reflectance of object without using a reference white standard. The overall performance of the invariant representation is examined in experiments using real-world objects including metals and dielectrics in detail. The feasibility of the representation for effective edge detection is introduced and compared with the state-of-the-art illumination-invariant methods.

Related Content

Bhargav Naidu Matcha, Sivakumar Sivanesan, K. C. Ng, Se Yong Eh Noum, Aman Sharma. © 2023. 60 pages.
Lavanya Sendhilvel, Kush Diwakar Desai, Simran Adake, Rachit Bisaria, Hemang Ghanshyambhai Vekariya. © 2023. 15 pages.
Jayanthi Ganapathy, Purushothaman R., Ramya M., Joselyn Diana C.. © 2023. 14 pages.
Prince Rajak, Anjali Sagar Jangde, Govind P. Gupta. © 2023. 14 pages.
Mustafa Eren Akpınar. © 2023. 9 pages.
Sreekantha Desai Karanam, Krithin M., R. V. Kulkarni. © 2023. 34 pages.
Omprakash Nayak, Tejaswini Pallapothala, Govind P. Gupta. © 2023. 19 pages.
Body Bottom