Open-source tool for eye image annotation

Abstract

Introduction: the tracking of the pupil center using videoculography images is widely used for the diagnosis of diseases of the nervous system. The difference between the automatically detected value of the pupil center and the reference value marked by a specialist (annotation) determines the accuracy of the diagnosis. The manual annotation process is very laborious, tedious, and prone to human error. Annotations are essential to develop and evaluate algorithms in the area of artificial vision, mainly those based on supervised learning, however, there are few interactive tools to perform reliable annotation of the center of the pupil. Objective: to develop an open source tool to annotate the center of the pupil. Method: The functional and non-functional requirements of the tool are defined and two algorithms are implemented for the semi-automatic annotation of the center of the pupil based on the ellipse and circle adjustment methods, from several points marked by the specialist. Results: The software application, called PUPILA, was developed in Python, from March 2020 to September 2020, and provides various auxiliary functions that facilitate the annotator's task. Conclusions: The new tool provides an agreeable and interactive environment to record the center of the pupil, guaranteeing comfort, accuracy and reduction of subjectivities in the specialist's work. It is open source and cross-platform, allowing it to be compatible with various devices and free to use. It has made it possible to annotate images from public databases and others acquired experimentally.

Keywords

• herramienta
• etiquetado de datos
• seguimiento ocular