English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Received: 25 January 2019 Accepted: 18 March 2019 The aim of the work is to identify the duplication in a video database with the aid of feature extraction techniques. The process includes extraction of image features (shape, color, and texture) for duplicate identification. The color contains 256 features, shape contains 200 features, the texture contains two different features namely gray-level co-occurrence matrix (GLCM) (22 features in 4 degrees) and grey-level run length matrix (GLRLM) (11 features) are extracted. In this paper, the preliminary work is to convert video into frames and then each frame into blocks subsequently including feature extraction. A query video is then considered for the same process of feature extraction and compared with the normal video. The distance between query video and normal video if found to be similar then the video identified as duplicate video. The results are performed for various evaluation matrix and plotted graphs are shown. The sensitivity value for whole feature extractions is 0.88, the specificity value for whole feature extractions is 0.83 and the accuracy value for whole extractions is 0.86. The entire process implemented in the working platform of MATLAB.

Assessment of Combined Shape, Color and Textural Features for Video Duplication