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El. knyga: Cognitively Inspired Video Text Processing

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

As technologies are fast advancing, the importance of text detection and recognition is receiving special attention from the researchers. Thus, one can see several real-time applications of video text processing which requires cognitive-based methods to find a solution. The main applications are (1) retrieving and indexing video based on semantic of the content of the video, (2) machine translation to assist foreigners, (3) assisting blind people to walk on the road freely without aid, (4) automatic vehicle driving, (5) license plate tracing to catch vehicles which violate the traffic signals, (6) monitoring the images posted on social media based on text and content of the images, (7) identifying the location based on the address of the street and shops, etc., (8) tracing players in the sports based on the jersey/bib number or text, and (9) in the same way, tracing the bib number in case of marathon and other events. For the above-mentioned applications, text detection and recognition in video and natural scene images is an integral part of the system.
Chapter
1. Introduction.
Chapter
2. Key Text Frame Selection from Video.
Chapter
3. Text and Non-Text Frame Classification in Video.
Chapter
4. Text Detection in Video.
Chapter
5. Text Detection in Images.
Chapter
6. Word and Character Segmentation.
Chapter
7. Video Text Type Classification.
Chapter
8. Video Text Enhancement for Recognition.
Chapter
9. Video Text Recognition.
Chapter
10. Conclusion and Future Directions.