As the text databases available to users become larger and more heterogeneous, genre becomes increasingly important for computational linguistics as a complement to topical and structural principles of classification. We propose a theory of genres as bundles of facets, which correlate with various surface cues, and argue that genre detection based on surface cues is as successful as detection b...

The detection of artificial text in video has been approached in many different ways, but each method shares a common thread. Text must first be segmented, then classified, and finally passed on to another algorithm depending on the overall task. Each method has shown varying degrees of success, however with no common data set and no standard metric for measuring results, comparison is difficul...

Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the probl...

While global characteristics of the speaker’s source and spectral features have been successfully employed in pathological voice detection, the underlying text has largely been ignored. In this work, we focus on experiments that exploit the text stimulus that is read by the subject. Features derived from text include the mean cepstral distortion of the subject from an average intelligible speak...

As the Internet help us cross cultural border by providing different information, plagiarism issue is bound to arise. As a result, plagiarism detection becomes more demanding in overcoming this issue. Different plagiarism detection tools have been developed based on various detection techniques. Nowadays, fingerprint matching technique plays an important role in those detection tools. However, ...

This study is about text detection and recognition in natural scene images. The main focus is on the detection, recognition and eventually, translation, of multi-oriented, multi-language and curvilinear text in such images. The study attempts to provide a solution that can detect and recognise such text since current leading mobile applications such as Word Lens and Google Goggles do not suppor...

It is well known that the text that appears in a video scene or is graphically added to it is an important source of semantic information for indexing and retrieval, notably in the context of video databases. This paper proposes an improved algorithm for the automatic extraction of text in digital video; its major strengths are its robustness in terms of text skew and its improved performance i...

In this paper we present the state of the art for detecting text in images and video frames and propose an edge-based algorithm for artificial text detection in video frames. First, an edge map is created using the Canny edge detector. Then, morphological filtering is used, based on geometrical constraints, in order to connect the vertical edges and discard false alarms. A connected component a...

This paper proposes a new detection technique for fadingin/out text regions fromMPEG1 bitstreams based on a Markov model. We focus on the properties that the luminance of a text region varies linearly in fading, and that text regions require larger amount of bits than non-text regions. These features are extracted directly from a target MPEG1 bitstream and they are fed into the Markov model to ...

In this paper, we present a texture-based text detection scheme for detecting text in natural scene images. This is a preliminary work towards a complete system of text detection, localization and recognition in order to help visually impaired persons. We have employed spatial histograms computed from gray-level co-occurrence matrices for texture coding and three classifiers have been evaluated...