Telefonaktiebolaget Lm Ericsson (publ)

Bhushan Ramnani

Aparna Varanasi

Anand Arun Joshi

Zheng Nie

Juan Flores

Xiaosong Zhu

Satish Haridass

Exemplary methods for automatically testing closed caption (CC) rendering includes receiving a set of one or more reference audio video (AV) streams from an AV source, and generating reference CC images from the set of one or more reference AV streams starting from a recording start time to a recording stop time. In one embodiment, the method further includes receiving a set of one or more test AV streams from the AV source, and generating test CC images from the set of one or more test AV streams starting from the recording start time to the recording stop time. In one embodiment, the methods further include determining whether the AV source is performing CC rendering properly by automatically comparing the test CC images against the reference CC images.

Caption rendering automation test framework

Exemplary methods and processing systems for determining whether an audio video (AV) source is performing closed captioning (CC) rendering properly, are described. An AV stream including one or more AV frames is received from the AV source; for each frame from the AV stream the following operations are performed: detecting a CC image in the frame; cropping the CC image from the frame; and outputting the CC image and metadata associated with the frame. A caption file is generated based on the AV stream, where the caption file includes captioning information for the AV stream. The CC image and metadata output for a frame from the AV stream are compared with CC information within the caption file related to that frame to determine whether the AV source is performing CC rendering properly.

Methods and systems for real time automated caption rendering testing

Exemplary methods of extracting closed caption (CC) image from a frame of an audio video (AV) stream are described. For all pixels of the frame, setting a color value of the pixels to a determined pixel value when the color value of the pixel is different from a background color value associated with CC image. A set edges is analyzed to identify one or more polygons. A polygon that contains text is determined from the one or more polygons. The frame is cropped along the polygon to obtain a CC image. Upon determination that the CC image is identical to another closed caption image a frame count associated with the other closed caption image is increased by 1; and upon determination that the CC image is not identical to the other CC image the closed caption image is stored along with a position and a time value as metadata information.

Automatic extraction of closed caption data from frames of an audio video (AV) stream using image clipping

Exemplary methods of extracting closed caption images from frames of an audio video (AV) stream are described. A first set of frames of a first AV stream including CC images and a second set of frames not including the CC images are received. Each pixel in the first frame is replaced with a dummy pixel, upon determination that a pixel at a corresponding position in the corresponding frame has a same color value to generate a filtered frame including dummy pixels and non-dummy pixels. First coordinates of the top-left most pixel of the first frame that is not a dummy pixel and second coordinates of the bottom-right most pixel of the first frame that is not a dummy pixel are determined. The filtered frame is cropped along the first and second coordinates to extract the CC image.

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Sunnyvale, CA, United States of America

Bhushan Ramnani