Efficient CIEDE2000-based Color Similarity Decision for Computer Vision

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Américo Pereira (Author) Other; Pedro Carvalho (Author) Other; Gil Coelho (Author) Other; Luís Corte-Real (Author) FEUP

Journal

Title: IEEE Transactions on Circuits and Systems for Video Technology

Pages: 1-14

ISSN: 1051-8215

Publisher: IEEE

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-00Q-H9E

DOI: 10.1109/tcsvt.2019.2914969

Abstract (EN): Color and color differences are critical aspects in many image processing and computer vision applications. A paradigmatic example is object segmentation, where color distances can greatly influence the performance of algorithms. Metrics for color difference have been proposed in the literature, including the definition of standards such as the CIEDE2000, which quantifies the change in visual perception of two given colors. This standard has been recommended for industrial computer vision applications, but the benefits of its application have been impaired by the complexity of the formula. This paper proposes a new strategy that improves the usability of the CIEDE2000 metric when a maximum acceptable distance can be imposed. We argue that, for applications where a maximum value, above which colors are considered to be different, can be established, then it is possible to reduce the amount of calculations of the metric, by preemptively analysing color features. This methodology encompasses the benefits of the metric while overcoming its computational limitations, thus broadening the range of applications of CIEDE2000 in both computer vision algorithms and computational resource requirements.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14