Visual Analysis System for Features and Distances Qualitative Assessment: Application to Word Image Matching

Frédéric Rayar (1) , Tanmoy Mondal (1) , Sabine Barrat (1) , Fatma Bouali (1, 2) , Gilles Venturini (1)

1 LIFAT - Laboratoire d'Informatique Fondamentale et Appliquée de Tours
2 Université de Lille, Droit et Santé

In this paper, a visual analysis system to qualitatively assess the features and distance functions that are used for calculating dissimilarity between two word images is presented. Computation of dissimilarity between two images is the prerequisite for image matching, indexing and retrieval problems. First, the features are extracted from the word images and a distance between each image to others is computed and represented in a matrix form. Then, based on this distance matrix, a proximity graph is built to structure the set of word images and highlight their topology. The proposed visual analysis system is a web based platform that allows visualisation and interactions on the obtained graph. This interactive visualisation tool inherently helps users to quickly analyse and understand the relevance and robustness of selected features and corresponding distance function in a unsupervised way, i.e. without any ground truth. Experiments are performed on a handwritten dataset of segmented words. Three types of features and four distance functions are considered to describe and compare the word images. Theses material are leveraged to evaluate the relevance of the built graph, and the usefulness of the platform.

Domaines: Informatique [cs]

Frédéric Rayar, Tanmoy Mondal, Sabine Barrat, Fatma Bouali, Gilles Venturini. Visual Analysis System for Features and Distances Qualitative Assessment: Application to Word Image Matching. 12th IAPR International Workshop on Document Analysis Systems, Apr 2016, Santorini, Greece. ⟨hal-01315646⟩