偏好膚色修正技術之研究

Abstract

在本文中，我們提出一套偏好膚色修正系統，能夠針對使用者的需要，對膚色做出適當調整。它利用了類神經網路來實現膚色偵測，不但準確而且快速。並且根據我們所設計的偏好膚色實驗，能夠定義出使用者對於不同光源狀況下所偏好的膚色。另一方面，我們也提出了一套利用模糊歸屬函數來根據影像亮度對膚色做分類的方法，應用在偏好膚色修正系統中。根據實驗結果，我們可以發現此系統對於不同人種的膚色偵測效果都很準確，而且在膚色調整的時候也不會產生瑕疵。

In this thesis, we propose a system of preferred skin color reproduction, which can adjust the skin color based on users’ preference. There are three main function blocks in this system: skin color detection, preferred skin color definition, and skin color correction. First, we adopt neural network to detect skin color in an efficient way. A fuzzy logic method is proposed to classify the detected skin color. Second, users’ preferred skin color on different lightness is defined through a deliberate experiment. Based on the conclusion of the experiment, the proposed system can properly modify the detected skin color to achieve users’ preference without producing boundary artifacts.