Abstract-Document image retrieval technology is extensively studied, but there is no report about Uyghur document image retrieval. Hu invariant moment features based document image retrieval scheme is proposed for Uyghur document images in this paper. Firstly, seven types of invariant moment features are extracted from Uyghur document images after obtaining image edge information using Canny edge operator. Then, the features are matched using Euclidean distance classifier and Feature distance classifier between query image with the target images. It is obtained the search results after ordering candidate images according to their similarity. Two types of experiments which are different in query image size are conducted using 1948 Uygur printed document images. The experimental results show that, the highest document image retrieval efficiency (to be get the matching rate of 100%) is obtained here when using the hole page document image is to be set as query image, and the matching rate is declined when sub images are selected as queries, the more the number of sub images, the lower the matching efficiency, and the retrieval efficiency is reached at minimum level when using one sixteenth of the document as query in our experiment. The experimental results indicated that Hu invariant moment features can effectively describe the nature of the Uyghur document images.
Until now, there has not been any major international effort that aims at comparing different signature verification methods systematically. However, most of the disclosed handwritten signature database is based on Latin, Chinese, Arabic and other languages. So creation of Uyghur off-line signature database plays very important role in estimating and comparing research results that was achieved by different groups of researcher. In this paper, the signature samples are collected by different age's people. For off-line Uyghur signature recognition and verification research, there are 500 persons genuine signature. (20 samples of each person), 185 persons simple forgery signature and skilled forgery signature (20 samples of each person), in total 17400 signature samples were collected. Each handwriting signature samples is scanned, stored with bmp file, and pre-processed (such as graying, noise reduction and binarization etc).The Uyghur signatures database very useful for designing a signature recognition and verification system that is optimized to verify Uyghur signatures.
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