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CH-5 – Software Testing and Running – Part-1

Posted on Author Ali Imran Comment(0)

Important Note: This article is part of the series in which TechReport.us discuss theory of Video Stream Matching.

5.1 Valid Input for VSM

AVI format videos are valid input for system. This is valid for both input source video and target video.

If target is not video and target is an image then valid format is BMP, JPEG, GIF.

5.2 Output of VSM

VSM provide information that if target video matches with source video, source video any part or not. Also if target image match with any frame of source video or not

This information makes available by producing a clip that represent that output.

5.3 How to Run the VSM

This application is developed on Windows XP environment. MATLAB 7.0 is the tool used for coding and implementation. System is P-3, 1000MHz

  1. This application is start by typing VSM on command prompt of MATLAB.

Figure 5.1 Command Prompt of MATLAB

  1. After pressing the enter key GUI will appear.

Figure 5.2 GUI of VSM

Ali Imran
Over the past 20+ years, I have been working as a software engineer, architect, and programmer, creating, designing, and programming various applications. My main focus has always been to achieve business goals and transform business ideas into digital reality. I have successfully solved numerous business problems and increased productivity for small businesses as well as enterprise corporations through the solutions that I created. My strong technical background and ability to work effectively in team environments make me a valuable asset to any organization.
https://ITsAli.com

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The VSM architecture comprises three main components: loading target videos, loading source videos, and loading target images into the classification model. Users can load target videos, source videos, or target images for classification purposes. Each component serves a specific function within the system, facilitating the comparison and analysis of video streams. The architecture is designed to handle various types of input data, ensuring flexibility and adaptability for different applications requiring video stream matching.
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CH-2 – Image Processing – Part-2

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Image processing encompasses image restoration, enhancement, and compression. It involves manipulating images already captured or generated, distinct from computer graphics, which generates synthetic images. Pixels in digital images have important relationships, including neighbors, adjacency, connectivity, regions, and boundaries. Pixels are considered connected if they share a similar criterion, such as grayscale value. Different types of adjacency include 4-adjacency, 8-adjacency, and mixed adjacency, the latter resolving ambiguities in the former. Paths between pixels can be defined based on adjacency type, such as 4-, 8-, or m-paths. Regions in images are connected sets of pixels, with boundaries defined as pixels with neighboring pixels outside the region. Edges, based on intensity discontinuities, are local concepts, while boundaries are global, forming closed paths.

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