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In this paper, we propose an image retrieval system that uses both local and global shape features to retrieve the most similar images from the database. To obtain both features, some pre-processing steps, such as object segmentation using Minimum Error Thresholding and border extraction, are firstly carried out. After that, the Grid Based method is used to(More)
In this paper, we propose an image retrieval system using the decomposition of shape information. First, the system extracts the boundary of the object using Minimum Error Thresholding and some morphological image processing method. After that, to extract the local feature, the image is divided into smaller areas. The feature relies on the discrete wavelet(More)
In this paper, we present a noise model for generating synthetic character databases to train Optical Character Recognition (OCR) systems. Nowadays, the emergence of new font typefaces requires an imperative task to automatically and rapidly generate synthetic training character databases. In addition, since the accuracy of the OCR systems deeply depends on(More)
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