An Evaluation of Methods on Detecting, Recognizing and Understanding Graphics Images in Technical Documents

Abstract

Proper document analysis is dependent on the accurate processing of each individual modalities [1], [2], [3]. Graphics images are such document modalities that illustrate visually information about the behavior of experimental systems, the trend of the financial market and etc. The automatic processing of information graphics aims to provide summarizations for such datasets with applications to document retrieval, enabling reading for visually impaired people and etc. In this paper we review existing chart analysis methodologies that work towards these goals. More specifically, we categorize the chart analysis methodologies into detection, recognition and understanding of graphics images. Graphics detection includes the localization of areas that potentially include chart figures. The area of graphics recognition focuses on identifying the legends and axis of inputs charts as well as the structural characteristics of their curves. Graphics understanding aims to capture the underlying message of input chart images and provide their summarizations. Additionally, we provide a discussion for each area of research about the characteristics and merits of their presented methodologies. Finally, we propose a comparison scheme that is based on subjective metrics that reflect the needs of modern applications.