Tag: image processing

The GUI of the Video Stream Matching (VSM) system includes buttons for loading target images and source videos, displaying them in the respective axes. Users can calculate wavelet, histogram, edge, and slope features for both source videos and target images. Additionally, buttons for different algorithms initiate the decision-making process, activating the statistical model. Results are displayed in the output window after completion of the process. The system provides comprehensive functionality for analyzing and comparing videos and images.

The GUI of the Video Stream Matching (VSM) system comprises 29 control buttons and 3 axes for displaying results. The Refresh Button clears all axes and unloads loaded data. The “Load Target Video” button prompts for selecting an AVI file to load as the test video. The loaded video plays in the “Axes Target Video/Frame,” with the Play Button performing the same function. The “Frames” button extracts frames from both the target and source videos. Lastly, the “Exit” Button closes the VSM application.

The Video Stream Matching (VSM) system accepts AVI format videos as valid input for both source and target videos. For target images, BMP, JPEG, and GIF formats are accepted. VSM outputs information indicating whether the target video matches any part of the source video, or if the target image matches any frame of the source video. The system is implemented in MATLAB 7.0 on a Windows XP environment, running on a P-3, 1000MHz system. To run the application, users type “VSM” on the MATLAB command prompt, triggering the appearance of a graphical user interface (GUI).

This research report and software implementation delve into video comparison techniques, focusing on mean frame extraction and key feature extraction within the Video Stream Matching (VSM) system. While the initial classification relies on a statistical approach, further improvements are needed, particularly in handling highly dynamic shots. Future work involves extensive testing with varied video datasets, exploration of motion-based features, and extension of similarity analysis to entire video sequences. With a shift towards video consumption, especially through mobile platforms, VSM emerges as a vital solution for managing video databases, highlighting the need for continued development in database design.

References – VSM