LARVAE IMAGE SEGMENTATION USING VLSI BASED ENSEMBLE CLUSTERING

Abstract

The study suggests a new way to separate larvae images by using a mix of VLSI-based ensemble
clustering methods. By incorporating Very Large-Scale Integration (VLSI) technology, the segmentation process
becomes faster. The ensemble clustering method combines different clustering techniques to improve accuracy
in identifying larvae structures. With VLSI, parallel processing is used, making the segmentation performance
better. This method aims to handle challenges like variations in larvae appearance and complicated
backgrounds. Tests show that VLSI-based ensemble clustering is effective in accurately separating larvae. Using
VLSI not only speeds up the process but also makes it suitable for real-time applications in fields like bug
science and ecology. The study helps advance image processing for automatic larvae analysis, offering a better
way for biological research to be more efficient and accurate.