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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/8530


    Title: 中英文名片商標的擷取及辨識
    Authors: 林家禎;Jian-Chen Lin
    Contributors: 資訊工程研究所
    Keywords: 商標的辨識;商標的擷取;名片的區塊切割;名片;小波轉換
    Date: 2001-06-29
    Issue Date: 2009-09-22 11:29:28 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 名片所傳達的訊息通常可分為二種,一種是屬於名片持有者的個人資訊,例如名片持有者姓名、地址、電話、電子郵件地址等等;另外一種資訊是屬於名片持有者其所屬公司的資訊,例如公司名稱、商標圖形、公司地址電話等等。 在名片中,公司名稱與商標圖形間具有一對一的對映關係,因此,如果我們可以識別出名片的商標圖形,則我們也可得知名片的公司名稱。此篇論文的目的主要是藉由名片之商標圖形的擷取及辨識來獲得與其相對應的公司名稱,並以此輔助名片上公司名稱欄位之OCR辨識結果的訂正。此外,對於同一家公司的名片而言,其名片的格式通常都是相同的,因此,我們可藉由名片的排版資訊來對名片作大分類。 商標圖形的擷取與辨識是此篇論文的重點所在,在擷取階段中,首先,我們必須先將輸入名片切割成幾個具有同質性資料的區塊,然後再分別給予每個區塊一些屬性,並以這些屬性所構成的一些規則來擷取出商標圖形。接下來,在商標圖形的辨識階段中,將所擷取出來的商標圖形首先正規化為 ,然後再利用小波轉換將其轉換成大小為 的小波係數矩陣。在我們的作業中,我們使用索引值為[0,0]的小波係數以及其他40個最大值的小波係數來作為商標圖形的特徵,最後,將所考慮的商標圖形之特徵與那些儲存在商標資料庫的商標圖形特徵作比較,以獲得辨識結果。 在實驗中,我們以90張名片來作測試,其中,有些為中文名片而有些則為英文名片。實驗結果可顯示,我們所提出之方法的有效性及可行性。 Business cards usually convey two kinds of information. One is the personal information, such as holder’s name, address, telephone number, e-mail address, etc. The other is the information of the company, such as company name, logo, address, telephone number, etc. In business cards, the relationship between company name and logo is one-to-one mapping. Thus, if we can recognize the logo, we can also know the company name of the business card. The goal of this thesis is to acquire the company name of any business card by means of extraction and recognition of its corresponding logo. Once we have acquired the company name of the business card from its corresponding logo, we can use it to correct the OCR result of company name in the business card. Besides, the formats of business cards are usually the same for the same companies. Thus, we can use the layouts that are extracted from the business cards to classify them. Extraction and recognition of logo are the focus of this thesis. In the extraction stage, an input business card is first segmented into many homogeneous blocks and each block is then given some attributes. Some rules are constructed based on the extracted attributes to extract the logo. In the recognition stage, the extracted logo is first normalized into and then transformed into matrix of wavelet coefficients. In our work, we use the coefficients of index [0,0] and 40 largest-magnitude as the features. Finally, the features of the considered logo are compared with those stored in logo database to obtain the recognition result. In our experiments, 90 business cards are tested. Some are Chinese formats and some are English ones. Experimental results reveal the feasibility and validity of our proposed method.
    Appears in Collections:[資訊工程研究所] 博碩士論文

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