西洋繪畫中的印象主義、立體主義及未來主義，是近代繪畫藝術的經典風格，對其後的藝術發展影響很大。其所產生的繪畫作品數量龐大，但對於此方面風格主義，以數位科技達到自動分類的研究不多。因此，本研究蒐集了這三種主義派別的圖案，加以整理分析，提出一種多重影像特徵集合，形成訓練資料，輸入類神經網路分類器進行運算，建立分類系統模型，以完成辨識新圖像是否屬於這三種繪畫主義之風格。本研究具體成果如下：1. 蒐集了三種主義派別的圖像，加以整理分析後，提出了一種多重影像特徵集合。2. 對圖像進行邊緣偵測、霍夫轉換、影像熵等影像處理，建立圖像樣本的特徵資料庫。3. 利用類神經網路予以分類，以特徵資料庫訓練以建立對圖像分類為印象主義、立體主義或未來主義的系統模型。4. 運用此系統模型，對圖像進行是屬於印象主義、立體主義或未來主義風格之分類。辨識準確度均達到相當不錯的水準，其中印象主義辨識成功率可達到92%，立體主義辨識成功率為85.71%，未來主義辨識成功率為64.52%，均能有相當之成效。 Impressionism, cubism and futurism are the three kinds of factions which are very important in the modern art history. Enormous painting artworks had created from these classes, but the research about auto-classifying the kind of faction the painting is belonged to is rare. This paper studies automatic classification on the three kinds of classical western paintings. An effective method for automatic image classification has been proposed. A set of multiple characteristics of the image collections is integrated to support the method. This paper has accomplished the followings:1. To collect, study and analysis enough number of digitized paintings out of the three different factions the images, and propose the multiple image characteristics set.2. To apply image processing techniques such as edge detection, image entropy, Hough transform and corner detection etc. to establish the characteristics set.3. To establish a neural network model as the classifier, train the network with the characteristics set, and create the classifier system.4. To apply the classifier to new images to verify the system’s performance.5. To reach a satisfactory level of the accuracies for the classifier, i.e., 92% for impressionism classification, 85.71% for cubism classification and 64.52% for futurism classification
