Cell Image Segmentation Using Watershed Algorithm and Canny Operator

Resource Overview

This program implements image segmentation techniques using watershed algorithm and Canny operator for cell image processing, enabling accurate cell counting and statistical analysis including cell quantity and area measurement through sophisticated edge detection and region-based segmentation approaches.

Detailed Documentation

This program focuses on the research and application of image segmentation techniques. It employs watershed algorithm combined with Canny operator to achieve precise segmentation of cell images, facilitating accurate counting and statistical analysis of cell quantity and area measurements. The implementation typically involves preprocessing steps like noise reduction using Gaussian filters, followed by Canny edge detection for boundary identification, and watershed transformation for region separation that handles overlapping cells effectively. By analyzing cell count and size distribution, researchers can obtain detailed cellular characteristics and further investigate biological properties and disease correlations. This program provides a straightforward yet efficient method for cell image processing, making significant contributions to advancements in cellular research fields through automated quantification capabilities.