Image Management Technique For Computer Aided Random-needle Embroidery Creation

Along with the rapid development of digital technology and a growing rapprochement between art and technology,it has become a research focus to study how to digitize the creation and production of traditional arts,which can promote the development of traditional arts.As a representative of traditional embroidery art,Random-Needle Embroidery has a unique embroidering shill,and it's good at characterizing the variation of color and texture,especially for oil paintings and photography works.But the Random-Needle Embroidery is hard to learn,hard to manufacture,and expensive for customers,which seriously restrict its development.How to assist the creation and production using computer technology has major cultural and economic significance.The computer aided creation for random-needle embroidery is essentially to complete the process of turning the original image into embroidery draft and then turning the embroidery draft into embroidery.The embroidery draft is the abstract of the structure and content of the original image,which is used to guide the simulation of the embroidery.Embroidery is the digital display on the simulation result.How to effectively store and manage the image information is the key to enhance the usability of the computer aided random-needle embroidery system.In this paper,we Hierarchical organize the Original images according to visual information,and design database management system to store and manage the image data,in order to help users to quickly find the target image information.The main achievements of this paper are threefold as follows.(1)The feature representation of image dataset.We extract global features and local features for artistic image dataset which often used as the creation material for random-needle embroidery respectively.And then,based on the spatial layout characteristics of the artistic image,we design a pyramid spatial match model to measure the similarity with different features,so that we can choose an appropriate feature representation for artistic images.At last we verify the face detection descriptor on artistic images.(2)The hierarchical organizing and browsing of image dataset.We propose a content-based hierarchical organization and display method for image dataset.Firstly,a suitable MLAP clustering mechanism is designed to construct the hierarchical clustering of image dataset to build the browsing tree structure.Then we display the images of every level by the means of t-SNE,MDS.At last we provide the local adjustment operation for the users to make up the semantic gap and individual differences.(3)Storage and management of image data.According to the relationship between data,we design database system to store and manage image data,and design information gathering mechanism to perfect image data's information,in order to assistant users to search the database according to sematic tag.