Related Experiment Video
Updated: Jun 4, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
A New Adaptive Structural Signature for Symbol Recognition by Using a Galois Lattice as a Classifier
Abstract:
In this paper, we propose a new approach for symbol recognition using structural signatures and a Galois lattice as a classifier. The structural signatures are based on topological graphs computed from segments which are extracted from the symbol images by using an adapted Hough transform. These structural signatures-that can be seen as dynamic paths which carry high-level information-are robust toward various transformations. They are classified by using a Galois lattice as a classifier. The performance of the proposed approach is evaluated based on the GREC'03 symbol database, and the experimental results we obtain are encouraging.
Related Concept Videos
Bewley Lattice Diagram
Structural Classification of Joints
A fibrous joint is where the adjacent bones are united by fibrous connective...
Lattice Centering and Coordination Number
Types of Unit Cells
Imagine taking a large number of identical...
Signal Flow Graphs
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...
Sign Test for Matched Pairs
To conduct the sign test, we first calculate the differences in value between...
Gauss's Law: Planar Symmetry
