Title: A colour transfer method of interior design based on machine learning

Authors: Tiesheng Liu

Addresses: Hunan City University, YiYang 413000, China

Abstract: In order to overcome the problems of large colour range, low structure similarity and poor objective evaluation index in the process of interior design colour transfer, this paper proposes a new method of interior design colour transfer based on machine learning. In this method, K-means algorithm is introduced to eliminate the uneven brightness area of the target image. The target image is processed by initial clustering, and the iterative threshold segmentation method is used to obtain the final clustering accurate target image. Combined with machine learning, the corresponding samples are selected on the two images to finish colouring, and the colour transfer of interior design is realised by referring to the coloured sample block. The experimental results show that the colour degree of the proposed method is maintained between 33 and 45, the structural similarity is always above 95%, and the comprehensive objective evaluation index value is close to 100%.

Keywords: machine learning; interior design; colour transfer; K-means algorithm.

DOI: 10.1504/IJICT.2023.131208

International Journal of Information and Communication Technology, 2023 Vol.22 No.4, pp.438 - 455

Received: 15 Mar 2021
Accepted: 21 May 2021
Published online: 01 Jun 2023 *

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