Machine Vision based Unsupervised Summarization of Wireless Capsule Endoscopy Video

Wireless capsule endoscopy is a medical procedure that uses a small, pill-sized capsule with a tiny camera inside to examine the inside of the digestive system. The capsule contains a camera that takes pictures as it moves through the digestive tract. The images are transmitted to a small recording device that the patient wears on a belt or shoulder strap. The recording device stores the images, which are later downloaded and examined by a doctor. The pill-sized camera records a video for eight to twelve hours. The purpose of this work is to investigate and
put into practise a technique for summarising the capsule endoscopy footage. The method clusters the video frames in order to accomplish this by looking for local maxima in the neighbouring distance graph that is generated from the colour histograms of each video frame. The method then determines the centroid frame for each cluster and produces a key-frame for each cluster. Visualising the conclusion of this investigation is its second objective. This is accomplished by placing each cluster on a timeline according to the size and calibre of the keyframe. The summary of the capsule endoscopy video is generated as a sequence of keyframes. These keyframes are representative frames of the video. The work also proposes a technique to assess the quality and the quantity of the keyframes extracted.

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The authors declare no conflict of interest.

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The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].

This work did not receive any external funding.