Automatic text detection and tracking in digital video

By Huiping Li, David S. Doermann, O. Kia. IEEE Transactions on Image Processing, 2000

662 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/f8f5c282dc11937d29183b955dc3e4fbb677571b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Media Technology

Citations in the corpus

ICDAR 2003 robust reading competitions (2003, background): “In recent years there has been some significant research into these general reading systems that are able to locate and/or read text in scene images [11, 2, 3, 4, 1, 10].”
Multimodal Video Indexing: A Review of the State-of-the-art (2004, methodology): “Optical Character Recognition (OCR) methods for detection of text in video frames can be divided into component-based, e.g., [78], or texture-based methods, e.g., [ 44 ].”
text Detection with Convolutional Neural Networks (2008, methodology): “Multilayer perceptrons (MLPs), for instance, have been used on top of wavelet features (Li et al., 2000) or Support Vector Machines (SVMs) on top of a carefully selected set of features (Lucas et al., 2005; Chen et al., 2004).”
Detecting and reading text in natural scenes (2004, background): “More relevant work is reported in [8], [9], [10], [22] ,[23].”
A comprehensive method for multilingual video text detection, localization, and extraction (2005, background): “, neural network [8] or a support vector machine [9], to classify text blocks and nontext blocks.”
Text information extraction in images and video: a survey (2004, methodology): “[51] 2000 Wavelet-based feature extraction and neural network for Scene text (slanted), localization, enhancement,”
Detecting texts of arbitrary orientations in natural images (2012, background): “There have been a large number of methods dealing with text detection in natural images and videos [18, 16, 30, 27, 22, 26].”
Localizing and segmenting text in images and videos (2002, neutral): “1 gives an overview of our text localization scheme.”
A framework for improved video text detection and recognition (2012, background): “Evaluation results for system performance of several stat-of-the-art video text detection methods [1, 4, 17, 19] have been reported in [1].”
A Hybrid Approach to Detect and Localize Texts in Natural Scene Images (2011, methodology): “Li et al. [18] proposed an algorithm for detecting texts in video by using first- and second-order moments of wavelet decomposition responses as local region features classified by a neural network classifier.”
Texture-Based Approach for Text Detection in Images Using Support Vector Machines and Continuously Adaptive Mean Shift Algorithm (2003, background): “While they are efficient at extracting texts, CC-based methods run into difficulties when the text is noisy, degraded, multicolored, textured, or touching itself or other graphical objects, which often occurs in digital images [4].”
Text Detection and Recognition in Imagery: A Survey (2015, methodology): “In a recent work, Lee et al. [130] proposed using a hybrid of features from gradients, Gabor filter energy, variance of Wavelet coefficients and edge intervals.”
A Unified Framework for Multioriented Text Detection and Recognition (2014, background): “Driven by the wide range of potential applications, scene text detection and recognition have been important research topics for decades [7], [8], [35]–[41] and have recently seen a surge in research efforts in the computer vision community [9]–[14], [17], [18], [20], [21], [26], [42].”
Scene text detection and recognition: recent advances and future trends (2015, background): “[38] 2000 can detect and track texts in videos only applicable to horizontal texts”
Fast and robust text detection in images and video frames (2005, methodology): “Although temporal information can be used to track text [12] and enhance its quality for recognition [15], it may not be a good feature for text detection because precise shot boundary detection is needed before identifying the appearance of a text line, which will increase the computation complexit”
Camera-based analysis of text and documents: a survey (2005, methodology): “perform wavelet decomposition on multiscale layers generated from the input grayscale image [54,55].”
Automatic detection and recognition of signs from natural scenes (2004, neutral): “In order to detect different sizes of text, the multiresolution/multiscale method has been used in text detection algorithms [13], [14], [28].”
Cascaded Segmentation-Detection Networks for Text-Based Traffic Sign Detection (2018, neutral): “[31] detect and track texts in videos.”