Robust character image retrieval method using bipartite matching and Pseudo-bipartite matching

Abstract

Studies have been actively undertaken on image retrieval from a large-capacity image database, particularly on image retrievals such as natural image retrieval, character image retrieval or trademark retrieval from a streaming image database. In retrieving a character image, either color or shape information is used for the key feature information. However, changes in the shape of a character image often makes it difficult to retrieve solely based on the shape information, requiring a new retrieval method where both color and shape information are taken into consideration. We present a highly effective method for retrieving or matching similar character images even when shape information differs substantially. In our approach, combined features of color and shape information are used for image retrieval; an image is first split into sectors; color information is extracted from the sector images followed by quantization using Parzen window to extract features; an image is then retrieved by means of bipartite matching using the features. Our results show the retrieval rate using the combined information increases substantially for matching natural or character images compared with the results obtained by the combination of two features independently.