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Proposing a practical approach to extract and read XML meta-data from sprite sheets using Blob detection algorithm
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This paper introduces a tool to semi-automatically generate meta-data from game sprite sheets. MuSSE is a tool developed to extract XML data from sprite sheet images with non-uniform – multi-sized – sprites. MuSSE (Multi-sized Sprite Sheet meta-data Exporter) is based on a Blob detection algorithm that incorporates a connected-component labeling system. Hence, blobs of arbitrary size can be extracted by adjusting component connectivity parameters. This image detection algorithm defines boundary blobs for each individual sprite in a sprite sheet. Every specific blob defines a sprite characteristic within the sheet: position, name and size, which allows for subsequent data specification for each blob/image. Those blobs are carefully optimized through an imbued threshold selection. This work also presents a parser to organize these meta-data into a readable solution for game engines. The parser is built to read XML metadata generated through MuSSE and allow developers to set up game objects that can be used by an engine. Several examples on real images illustrate the performance of the proposed algorithm and working tool.
Sociedade Brasileira de Computacao - SB
Title: Proposing a practical approach to extract and read XML meta-data from sprite sheets using Blob detection algorithm
Description:
This paper introduces a tool to semi-automatically generate meta-data from game sprite sheets.
MuSSE is a tool developed to extract XML data from sprite sheet images with non-uniform – multi-sized – sprites.
MuSSE (Multi-sized Sprite Sheet meta-data Exporter) is based on a Blob detection algorithm that incorporates a connected-component labeling system.
Hence, blobs of arbitrary size can be extracted by adjusting component connectivity parameters.
This image detection algorithm defines boundary blobs for each individual sprite in a sprite sheet.
Every specific blob defines a sprite characteristic within the sheet: position, name and size, which allows for subsequent data specification for each blob/image.
Those blobs are carefully optimized through an imbued threshold selection.
This work also presents a parser to organize these meta-data into a readable solution for game engines.
The parser is built to read XML metadata generated through MuSSE and allow developers to set up game objects that can be used by an engine.
Several examples on real images illustrate the performance of the proposed algorithm and working tool.
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