Current Issue Cover


摘 要
Reviews on methods of feature extraction and researches of affective analysis for the painting

jiachunhua,guoxiaoying(College of Engineering, Shanxi University)

Image classification and affective analysis are the hot issues in the field of computer vision, which provide effective methods for the research of digital painting and play very important roles in the art protection and painting innovation for the human beings. Brush strokes, color, shape, texture, and white space are the very important visual features of the paintings, the classification based on these visual features can help us to better identify painting style and painter, analyze painting affection, further understand the meanings of painting creation and inherit cultural. The contributions of this paper are as follows: (1) The paper firstly shows the different representation modes of Chinese painting and western painting, and then analyzes why these two modes are different. The reasons mainly derive from the different cultural backgrounds and the different ways of thinking. These analyses offer a starting point for feature extraction and affective analysis of painting image; in addition, the paper sums up the painting database commonly used in the present study. Chinese traditional painting has its unique artistic expression technique, which makes the painting have the artistic effect of "false or true complement" by skillfully using white space. In addition, traditional Chinese painting attaches importance to the combination of calligraphy and poetry, decorated with a seal, and it emphasizes the connection between art and nature to present spirit by form. The line is the basic modeling way and the color is the auxiliary characteristic for Chinese traditional painting, which does not pay great attention to the bright and dark change of the light and shadow. Besides, the line is a form of expression for the traditional Chinese painting affective characteristics. For an appreciator, Chinese traditional painting needs more association and imagination, rather than visual effect. Chinese painting style mainly includes two major categories of traditional ink painting and mural, the formation of the ink and wash style is mainly distinguished by the representative painters, who are Qi baishi, Zheng banqiao, Xu beihong, Wu guanzhong, Wu changshuo, Huang gongwang, and so on; and mural research is represented by Chinese Dunhuang mogao grottoes murals with distinctive national style, which have rich and colorful content and the form of painting, they are expectations of people"s good wishes. Western painting is very different from traditional Chinese painting style. Traditional western painting highlights realism, emphasizing similar appearance, reproduction, space time and effect of light color. Western painting attaches great importance to the use of the change of color, light and shadow to show images, besides that, elaborately and tactfully use of color also can reflect the painting affection. Because of the shading of object, the whole painting has a better sense of texture and space. Contrary to the traditional Chinese painting, western painting gives the viewer more visual effects. Western painting style is associated with the development of literature and art movement, the formation of painting style is mainly divided into baroque style, three-dimensional style, impressionist style, romantic style, the rococo style, the Renaissance style, etc. (2) The paper outlines machine learning methods of the support vector machines, decision tree, artificial neural networks and deep learning, K nearest neighbor classification, which are commonly used in painting classification. The paper also analyzes the advantages and disadvantages of all kinds of methods. Besides, the paper reviews in detail the research status, the development of feature extraction technology and classification method for Chinese and western paintings from the view of the characteristics of the brushstrokes, color features, shape features and texture features and so on. This paper describes briefly the commonly used evaluation methods of the painting classification model, which are error rate and accuracy, precision and recall ratio, P-R curve and F1 measurement, ROC curve and AUC. Furthermore, some commonly used evaluation indexes in the current researches are analyzed. Computer vision technology has the distinct advantage in the fields of object recognition, scene classification, image classification, image affective and semantic analysis, which can make meaningful judgement for the perception target images and scenes by simulating human intelligent of vision. The essential feature of the image is the key of right judgement. As a kind of image resource, the selection of painting characteristics is very important for the painting classification and affective analysis. Machine learning is closely related with painting feature selection and classification research, which investigates how to use a computer to simulate or realize people"s learning activities, so that it can acquire new knowledge and skills. Machine learning is widely used in the field of each branch of artificial intelligence. (3) The paper probes into the affective investigation of western painting based on color features, and provides an efficient idea for the affective analysis of the Chinese traditional painting. Painting can reflect the objective social life and rich affection of the painter, using computer intelligence to analyze painting affection can help us better understand the history and culture of various periods. Chinese painting has its unique style, with the characteristics of the ink brush stroke, shade of ink, white space of the painting, painting content, and so on, which all can also convey different affections that the painter want to express. Combining the cognitive and psychological knowledge, methods of the image feature extraction can also realize affective analysis and affective extraction of the Chinese ink and wash painting. (4) Based on the views of the database of the painting classification, the classification goal and the limitation of affective analysis of the painting, the paper puts forward existing problems and challenges in the study of painting classification and painting affective, meanwhile discusses the solutions to the existing problems. In the further study of the painting classification, especially in the research of the traditional Chinese ink painting affective analysis and painting art creation, the content of this article can play a certain enlightening and guiding role.