Text Localization and Extraction from Still Images using Fast Bounding Box Algorithm

Paliwal, Sonal; Singh, Rajesh; Mandoria, Hardwari Lal

doi:10.13005/ojcst/9.02.06

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2017

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“…With their proposed method, the computational complexity is comparatively less and video summarization is very compact. Paliwal, et al [2], Text extraction from still images and videos are on high demand these days in the area of multimedia for data retrieval and many other. Text extraction from the videos is a challenging task in image processing because of complex and sometimes highly illuminated background in videos it is quite complicated to extract text from the running video.…”

Section: Literature Surveymentioning

confidence: 99%

Review of Purposed Method for Key Frame Extraction From Videos

2017

ijarcs

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In recent days, vision based surveillance in public spaces has dramatically increased due to its wide applications such as traffic system management, terrorism/crime deterrence, and crowded activity monitoring and so on. These surveillance videos often contain a large amount of frames. Taking an example of a frame of 25fps, there are 250*3600=90,000 frames in total for one hour of video. The huge volume of video data is a barrier to many practical usages. So, work on key frame extraction going on to extract key frames from videos which give an overall summarization of a video.

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Section: Literature Surveymentioning

confidence: 99%

Review of Purposed Method for Key Frame Extraction From Videos

2017

ijarcs

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Text Localization and Extraction from Still Images using Fast Bounding Box Algorithm

Cited by 1 publication

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Review of Purposed Method for Key Frame Extraction From Videos

Review of Purposed Method for Key Frame Extraction From Videos

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