Text information in natural scene images serves as important clues for many computer vision applications such as content-based image retrieval, tourist translator, and assistive navigation. Extraction of such information from natural scene images, involves number of sub stages represented by text information extraction (TIE) system. However, performance of such system is greatly influenced by t...

Scene text contains significant and beneficial information. Extraction and localization of scene text is used in many applications. In this paper, we propose a connected component based method to extract text from natural images. The proposed method uses color space processing. Histogram analysis and geometrical properties are used for edge detection. Character recognition is done through OCR w...

There is extensive interest in automating the collection, organization and summarization of biological data. Data in the form of figures and accompanying captions in literature present special challenges for such efforts. Based on our previously developed search engines to find fluorescence microscope images depicting protein subcellular patterns, we introduced text mining and Optical Character...

An end-to-end method for multi-language scene text localization, recognition and script identification is proposed. The approach is based on a set of convolutional neural nets. The method, called E2E-MLT, achieves state-of-theart performance for both joint localization and script identification in natural images and in cropped word script identification. E2E-MLT is the first published multi-lan...

The transport and magnetic properties of the tetragonal Fe[Formula: see text]S were investigated using magnetoresistivity and magnetization within [Formula: see text] K, [Formula: see text] 70 kOe and [Formula: see text] 3.0 GPa. In addition, room-temperature x-ray diffraction and photoelectron spectroscopy were also applied. In contrast to previously reported nonmetallic character, Fe[Formula:...

The text detection and localization plays a major role in video analysis and understanding. The scene text embedded in video consist of high-level semantics and hence contributes significantly to visual content analysis and retrieval. This paper proposes a novel method to robustly localize the texts in natural scene images and videos based on sobel edge emphasizing approach. The input image is ...

In this paper, we propose a gradient difference based approach to text localization in videos and scene images. The input video frame/ image is first compressed using multilevel 2-D wavelet transform. The edge information of the reconstructed image is found which is further used for finding the maximum gradient difference between the pixels and then the boundaries of the detected text blocks ar...

Observing that text in virtually any script is formed of strokes, we propose a novel easy-to-implement stroke detector which is significantly faster and produces significantly less false detections than the detectors commonly used in scene text localization. First, stroke-specific keypoints are efficiently detected. Text fragments are subsequently extracted by local thresholding guided by keypo...