The automatic Thai basketry detection and recognition on the local wisdom video

To retrieve the videos having content relating to Local Thai basketry, creating video´s indexes is vital because indexes allow users to more quickly find video for specific individuals. In this work, it aims to propose a novel methodology of video indexing. The proposed methodology consists of two main processing stages. The first stage is to capture video frames having the Thai basketry, and then classify them into many individual groups, because local Thai basketry can be classified into many types depending on its usability and pattern. This stage is driven on using color and texture, which are processed through the Artificial Neural networks (ANNs). The second stage is to recognize the basketry shape by chain code and template matching analysis on the object´s shape in order to use them as video indexing. Finally, the proposed methodology is experimented on 41 local wisdom videos having 76 shorts and 4,196 frames. After testing by recall, precision, and F-measure, they show the satisfactory results for recall, precision, and F-measure as 78.64%, 83.88%, and 81.18%, respectively.