Research on the Identification of Hand-Painted and Machine-Printed Thangka Using CBIR

Abstract

Thangka is a unique painting art form in Tibetan culture. As Thangka was awarded as the first batch of national intangible cultural heritage, it has been brought into focus. Unfortunately, illegal merchants sell fake Thangkas at high prices for profit. Therefore, identifying hand-painted Thangkas from machine-printed fake Thangkas is important for protecting national intangible cultural heritage. The paper uses Content-Based Image Retrieval (CBIR) techniques to analyze the color, shape, texture, and other characteristics of hand-painted and machine- printed Thangka images, in order to identify Thangkas. Based on the database collected and established by this project team, we use Local Binary Pattern (LBP) texture analysis combined with the color histogram of Hue,aturation, Value (HSV) space, scale invariance, K-Means clustering, perceptual Difference Hash (DHASH) and other algorithms to extract the color lines and texture features of Thangka images, in order to identify hand-painted and machine-printed Thangkas. Three algorithms, LBP algorithm and HSV algorithm and DHASH algorithm, are compared, and the experimental results show that the color histogram algorithm based on HSV space is efficient. This algorithm can be applied broadly to retrieve and identify hand-painted Thangkas and help protect this precious intangible cultural heritage.