文字辨識系統之設計與製作

Design and Implementation of a Novel Text Recognition System

詹朝淵(JHAO-YUAN JHAN)

指導教授 ： 沈榮麟

國立臺北大學/電機資訊學院/資訊工程學系/碩士(2016年)

摘要

最近幾年存在很多方法辨識場景的阻礙物，在這篇論文，我們提出一個以影像圖來辨識文字的方法。首先，我們利用歐蘇(Otsu)演算法之二值化處理影像的邊緣偵測，以及結合K群聚參數集合。第二，利用改良式K群聚演算法偵測圖像中的區塊是否有文字，在複雜背景中具有良好的濾波功能。第三，經由梯度柱狀圖統計文字所有角度分佈。接著，根據梯度柱狀圖所統計出來的所有角度產生機率值。最後，利用角度產生之機率值經由隱藏式馬可夫模型(HMM)達到文字辨識之目的;經實驗結果發現，我們所提出的方法優於目前已有的其他方法。

關鍵字

邊緣偵測 ； 隱藏馬可夫模型 ； 影像處理 ； K群聚 ； 文字辨識

並列摘要

In order to identify scene texts from the background interferences, many existing methods have been presented in the recent years. In this thesis, a novel text recognition method is proposed. First, Otsu edge detection is applied to the image binarization and the parameters (i.e. weights) found in a K-cluster. Second, the modified K-cluster algorithm is used to detect the text from an image. The complex background is filtered out as well. Third, the detected text gradients are evaluated by HoG (Histogram of Gradient). Accordingly, the distribution of the detected text gradients is generated. Finally, the gradient distribution is utilized by HMMs to recognize the text. The proposed approach can outperform the existing methods.

並列關鍵字

Edge detection ； Hidden Markov model ； Image processing ； K-cluster ； Text recognition

參考文獻

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