Extraction of light and specific features for historical image indexing and matching

This paper proposes a new feature extraction technique for indexing and matching historical images. The complexity of these historical images troubles the existing indexing approaches due to their line patterns. Our indexing method relies on the global segmentation integrated with the knowledge of edge density to deal with the line patterns and eliminate over-segmented regions. Then the historical images are represented by a set of ROI descriptors and the retrieval is performed by matching sorted features. Experiments and system evaluations with and without ground truth are presented and discussed.