Script Identification of Multi-Script Documents: A Survey <s> 3) TEMPLATE MATCHING FEATURES <s> We describe an automated script identification system for typeset document images. Templates for each script are created by clustering textual symbols from a training set. Symbols from new images are compared to the templates to find the best script. Our current system processes thirteen scripts with minimal preprocessing and high accuracy. <s> BIB001 </s> Script Identification of Multi-Script Documents: A Survey <s> 3) TEMPLATE MATCHING FEATURES <s> Document Script Identification (DSI) is a very useful application in document processing. This paper presents a method for this application that uses a new noise tolerant feature, the Downgraded Pixel Density feature. Compared to other features widely used in existing DSI solutions, this new feature is much more robust to variations in slant, font and style of printed documents. Experimental results show that the method achieves promising identification performances. <s> BIB002 </s> Script Identification of Multi-Script Documents: A Survey <s> 3) TEMPLATE MATCHING FEATURES <s> This paper proposes improved Template Matching algorithm that applied for the automatic extraction of text from image and video frames. Optical Character Recognition using Template Matching is a system model that is useful to recognize the character, alphabet & special character by comparing two images of the alphabet. The objectives of this system model are to develop a model for the Optical Character Recognition (OCR) system and to implement the Template Matching algorithm in developing the system model. The template matching techniques are more sensitive to font and size variations of the characters than the feature classification methods. This system tested the 25 videos with 370 video frames for each video. In this system 91% of the Character gets recognized successfully using Texture-based approaches to automatic detection, segmentation and recognition of visual text occurrences in images and video frames. <s> BIB003
In the template-based approach, an unknown pattern is superposed directly on the ideal template pattern and the degree of correlation between the two is used for classification. In general these methods have advantages in distinguishing similar scripts although they are strongly sensitive to the font and size variations of characters  , BIB003 , BIB001 , BIB002 .