This paper presents an automatic recognition method for color text characters extracted from
scene images, which is robust to strong distortions, complex background, low resolution and …

In this paper, we propose a method based on gradient vector flow for video character
segmentation. By formulating character segmentation as a minimum cost path finding …

Text embedded in multimedia documents represents an important semantic information that
helps to automatically access the content. This paper proposes two neural-based optical …

The visualization of high resolution video on small mobile devices is still a great challenge
today. Most critical are the limited display resolution and different aspect ratios of handheld …

This work aims at helping multimedia content understanding by deriving benefit from textual
clues embedded in digital videos. For this, we developed a complete video Optical …

The curvature scale space (CSS) technique, which is also part of the MPEG-7 standard, is a
robust method to describe complex shapes. The central idea is to analyze the curvature of a …

In this paper, a natural scene character recognition method using convolutional neural
network (CNN) and bimodal image enhancement is proposed. CNN based grayscale …

Word segmentation has become a research topic to improve OCR accuracy for video text
recognition, because a video text line suffers from arbitrary orientation, complex background …

This paper presents a graph based scheme for color text recognition in images and videos,
which is particularly robust to complex background, low resolution or video coding artifacts …

This paper presents an automatic segmentation system for characters in text color images
cropped from natural images or videos based on a new neuronal architecture insuring fast …