2002
DOI: 10.1109/tnn.2002.1021896
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A spatial-temporal approach for video caption detection and recognition

Abstract: Abstract-We present a video caption detection and recognition system based on a fuzzy-clustering neural network (FCNN) classifier. Using a novel caption-transition detection scheme we locate both spatial and temporal positions of video captions with high precision and efficiency. Then employing several new character segmentation and binarization techniques, we improve the Chinese video-caption recognition accuracy from 13% to 86% on a set of news video captions. As the first attempt on Chinese video-caption re… Show more

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Cited by 107 publications
(2 citation statements)
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“…The wave plate group is mounted on a computer-controlled hollow motor that rotates to achieve the desired input polarization state for the SMF. The PM identifies and records the Stokes vector using OCR technology, which is then converted into the corresponding output polarization state [14] . This process is automated, enabling efficient and accurate measurement of multiple input-output polarization state combinations.…”
Section: Methodsmentioning
confidence: 99%
“…The wave plate group is mounted on a computer-controlled hollow motor that rotates to achieve the desired input polarization state for the SMF. The PM identifies and records the Stokes vector using OCR technology, which is then converted into the corresponding output polarization state [14] . This process is automated, enabling efficient and accurate measurement of multiple input-output polarization state combinations.…”
Section: Methodsmentioning
confidence: 99%
“…Deep learning models (i.e., deep neural networks) have been widely studied and applied to several computer vision tasks [35−39] , such as image classification [35] , object detection [36] , and image restoration [38] . In general, the pipeline of the deep neural networks can be seen in Fig.…”
Section: Deep Learning Modelsmentioning
confidence: 99%