By Tong Lu, Shivakumara Palaiahnakote, Chew Lim Tan, Wenyin Liu (auth.)
ISBN-10: 1447165144
ISBN-13: 9781447165149
ISBN-10: 1447165152
ISBN-13: 9781447165156
This e-book provides a scientific advent to the most recent advancements in video textual content detection. starting with a dialogue of the underlying thought and a short heritage of video textual content detection, the textual content proceeds to hide pre-processing and post-processing recommendations, personality segmentation and popularity, identity of non-English scripts, strategies for multi-modal research and function assessment. The detection of textual content from either average video scenes and artificially inserted captions is tested. numerous purposes of the know-how also are reviewed, from registration code acceptance and highway navigation counsel, to activities research and video advertisements platforms. positive aspects: explains the elemental idea in a succinct demeanour, supplemented with references for extra studying; highlights functional innovations to assist the reader comprehend and advance their very own video textual content detection platforms and purposes; serves as an easy-to-navigate reference, featuring the cloth in self-contained chapters.
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Additional resources for Video Text Detection
Example text
For other methods that consider video scene structures as scene contexts for text detection, a more general segmentation algorithm is potentially required to partition each video scene image into several meaningful parts such as street, building, and sky to reduce the searching space. After segmentation, each video frame can be considered to consist of homogeneous segments. By filtering the monochrome segments whose widths and heights are too large or too small to be instances of video characters (Fig.
This is because there are so many possibilities when extracting video texts that have variations in font style, size, color, orientation, and alignment or from a textured background with low contrast. Moreover, suppose the input of a text detection system is a sequence of video frames, the texts in the frames may or may not move, and the video itself can be in low resolution. These variations make the problem of automatic video text detection extremely difficult, and we thus need video preprocessing to reduce the complexity of the succeeding steps probably consisting of video text detection, localization, extraction, tracking, reconstruction, and recognition.
4. Next, Sect. 5 discusses motion analysis which is helpful to improve the efficiency or the accuracy of video text detection by tracing text from temporal frames. Finally, Sect. 6 concludes this chapter. 1 Preprocessing Operators Image (or video frame) preprocessing is the term for operations on images (or video frames) at the lowest level of analysis. 1 Preprocessing Operators 21 undesired degradations and simultaneously enhancing specific text relevant features. In this section, we will introduce several typical preprocessing operators that are either important for enhancing image features or helpful in suppressing information that is not relevant to video text detection.
Video Text Detection by Tong Lu, Shivakumara Palaiahnakote, Chew Lim Tan, Wenyin Liu (auth.)
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