Script Identification of Multi-Script Documents: A Survey <s> A. SCRIPT IDENTIFICATION IN PRINTED DOCUMENTS <s> Script identification is an important step in multi-script document analysis. As different textures present in text portion of a script are the main distinct features of the script, in this paper, we proposed a new algorithm for printed script identification based on texture analysis. Since local patterns is a unifying concept for traditional statistical and structural approaches of texture analysis, here the basic idea is to use the histogram of the local patterns as description of the script stroke directions distribution which is the characteristic of every script. As local pattern, the basic version of the Local Binary Patterns (LBP) and a modified version of the Orientation of the Local Binary Patterns (OLBP) are proposed. A Least Square Support Vector Machine (LS-SVM) is used as identifier. The scheme has been verified on two databases. The first or training database is a database with 200 sheets of 10 different scripts. The scripts font is provided by the Google translator. The second or test database has been obtained by scanning different newspapers and books. It contains 5 common scripts among 10 different scripts of the first database. From the experiment we obtained encouraging results. <s> BIB001 </s> Script Identification of Multi-Script Documents: A Survey <s> A. SCRIPT IDENTIFICATION IN PRINTED DOCUMENTS <s> Script identification is a very important field in the area of pattern recognition & document image analysis. Commendable work has been proposed and implemented to recognize various common scripts in unilingual, bilingual and multilingual contexts. So far, diminutive work has been presented for Kashmiri script identification. In this paper, we are describing and experimentally testing our approach for identification of Kashmiri script with respect to English script which comprises a text document image. Two important and simple features are used for identification of scripts: Horizontal Profile Coefficients (Peaks) & Horizontal Profile Valleys. <s> BIB002
Most script identification research was carried out on printed documents. The main sources of printed documents include books, magazines, journals, dictionaries, etc.. Some researcher prepared multi script texts using automatic translating software BIB001 or other software BIB002 firstly, then multi script documents are obtained as computer printouts. Since the diversity of scripts and the deficiency of available public databases, most of the researcher built their own databases/datasets, as Table 3 summarizes.