The indexing and retrieval of document images: a survey
Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
Imaged Document Text Retrieval Without OCR
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document Image Retrieval Based on Density Distribution Feature and Key Block Feature
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Document Image Retrieval through Word Shape Coding
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Method for Image Retrieval Based on Shape Decomposition
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02
A Document Image Retrieval System
Engineering Applications of Artificial Intelligence
| Hi-index | 0.00 |
This paper presents a novel approach to Amharic document image retrieval by taking the morphology of the language into account. In addition to the general problems and issues concerning document image retrieval systems, Amharic poses further difficulties in modeling retrieval systems due to its complex morphology. We encode the morphological characteristics of the language to improve query formulation and image database indexing. In this work, morphological generator is used to automatically synthesize surface words from a lexicon containing Amharic root forms resulting in surface word image features coded with their respective root forms. Using this morphological coding, document word images and query terms are processed to be represented by their root forms. In the process of indexing and query formulation, cosine similarity is used for comparing word image features extracted from vertical projection, upper bound profile and lower bound profile. The proposed system is tested by using real-life Amharic documents collected from various sources and experimental results are reported.