Word shape recognition for image-based document retrieval

In this paper, we propose a word shape recognition method for retrieving image-based documents. Document images are segmented at the word level first. Then the proposed method detects local extrema points in word segments to form so-called vertical bar patterns. These vertical bar patterns form the feature vector of a document. Scalar product of two document feature vectors is calculated to measure the pair-wise similarity of document images. The proposed method is robust to changing fonts and styles, and is less affected by degradation of document qualities. Three groups of words in different fonts and image qualities were used to test the validity of our method. Real-life document images were also used to test the method's ability of retrieving relevant documents.

• Type: Conference
• Year: 2001
• Where: ICIP
• Authors: Weihua Huang, Chew Lim Tan, Sam Yuan Sung, Yi Xu
• Keywords: Document Feature Vectors, ICIP 2001, Image Processing, Real-life Document Images, Vertical Bar Patterns