Volume 3, Issue 1 (1-2017)                   ITCMS 2017, 3(1): 10-1 | Back to browse issues page

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Saravanan D. An Efficient Video Content Retrieval Using Data Mining Image Key Frame Clustering Technique. ITCMS. 2017; 3 (1) :10-1
URL: http://itcms.europeansp.org/article-11-168-en.html
Faculty of Operations & IT, IFHE University, IBS Hyderabad, Telangana.
Abstract:   (530 Views)
Video data retrieval or video data content mining has become more thirsted area in recent years. This is due to the rise in the amount of digital video data available. Daily production of video data is rapidly increasing owing to the emergence of digital devices like cameras and cell phones. The availability of video content in the web is also growing due to development of technology. Today videos can be downloaded and played on many special devices, and web sites allow the users to easily upload and download videos. To handle this situation effectively, many researchers have worked on retrieval, indexing and categorizing the video content. This area of study requires urgent attention because of the large amount of video data and restricted man power to retrieve the exact video content. The retrieval process is not an easy task, because multimedia data content consists of a combination of audio, video, text, image and motion. From this huge multimedia content, retrieving video data is a challenging task. This research paper develops a new mechanism for effective video content retrieval using hierarchical clustering technique. This work focuses on extracting the key frame values from both trained video frame and query image. It has shown to produce better results than previous techniques.
Full-Text [PDF 594 kb]   (210 Downloads)    
Type of Study: Research |
Received: 2019/08/8 | Accepted: 2019/08/8 | Published: 2019/08/8

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