Connected Filtering Based on Multivalued Component-Trees

Towards Connected Filtering Based on Component-Graphs

In recent works, a new notion of component-graph has been introduced to extend the data structure of component-tree –and the induced antiextensive filtering methodologies– from grey-level images to multivalued ones. In this article, we briefly recall the main structural key-points of component-graphs, and we present the first algorithmic results that open the way to the actual development of co...

Connected Component Based Word Spotting on Persian Handwritten image documents

Word spotting is to make searchable unindexed image documents by locating word/words in a doc-ument image, given a query word. This problem is challenging, mainly due to the large numberof word classes with very small inter-class and substantial intra-class distances. In this paper, asegmentation-based word spotting method is presented for multi-writer Persian handwritten doc-...

Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based sc...

Shape-Based Analysis on Component-Graphs for Multivalued Image Processing

The extension of mathematical morphology to multivalued images is an important issue. This is particularly true in the context of connected operators based on morphological hierarchies, which aim to provide efficient image filtering and segmentation tools in various application fields, e.g.(bio)medical imaging, remote sensing, or astronomy. In this article, we propose a preliminary study that d...

On Multivalued Nonexpansive Mappings in ℝ-Trees