本論文提出一個新穎的印花布的自動化影像分析系統，此系統能對印花布影像進行自動化分色及辨識重複圖案。此系統是以掃描器進行影像的取得，所使用到的彩色格式有紅綠藍(RGB)及色調飽和度亮度(HSI)兩種。在分色上，本論文是以兩種方式進行，一是以非監督式聚類法(Unsupervised Clustering Method)於印花布的RGB影像上進行分色。另一是先以基因演算(Genetic Algorithm)法找出與原織物HSI影像有相同顏色分佈的較小HSI子影像，再以遞迴式區域分裂法(Region Splitting Method)進行分色。在重複圖案的辨識上，是以非監督式分類法及模板匹配法(Template Matching)找出相同圖案元件的分佈，再以霍弗(Hough)轉換法找出重複圖案的切割位置及尺寸，然後於印花圖案影像中切割出矩形的單位重複圖案的影像。最後依顏色類別產生相對應的黑圖重複單位，然後再擴展成製版用的黑圖。由實驗結果可知，本系統能自動化且快速地完成印花布影像的自動化分色及重複圖案的辨識。

This dissertation proposes a novel automatic image analysis system for printed fabrics that can automatically make color separation and identify repeat patterns. This system uses a scanner to obtain color images of printed fabrics. There are two types of color models, RGB (red, green, blue) and HSI (hue, saturation, intensity). In the color separation, this system can be operated by two ways. One is conducted by an unsupervised clustering method on the RGB image of the printed fabrics. Another uses a genetic algorithm to search for a smaller HSI sub-image with the same color distribution of the printed fabrics, and then the color separation is conducted by use of a recursive region splitting method. In identifying the repeat patterns, an unsupervised classification method and a template matching method are used to identify distributions of same pattern elements, and then a Hough transform method is applied to obtain the cut positions and dimensions of repeat patterns. Next, an image of the repeat pattern is cut out of the fabrics’ image. Finally, the repeated units of black pictures are generated based on color categories and are then expanded to become black pictures used for plate making. According to the experimental results, this system can rapidly and automatically complete color separation and identify repeat patterns for printed fabrics’ images.

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