Cellular Microscopy Image Segmentation Project – Key Vocabulary

Five vocabulary flashcards covering core terms and requirements from the image-segmentation project notes.

Image Segmentation (Microscopy)

The process of partitioning microscopic images into meaningful regions—such as white blood cells, red blood cells, and plasma background—to facilitate medical analysis and diagnosis.

Fuzzy C-Means (FCM) Clustering

An unsupervised classification algorithm that assigns each pixel a degree of membership to multiple clusters, commonly used to segment biological images into cell types and background.

Bidimensional Color Histogram Analysis

A segmentation approach that examines two-dimensional histograms in a chosen color space to distinguish image regions based on combined color-channel distributions.

OpenCV

An open-source computer-vision library (C++/Python) offering extensive functions for image processing, feature extraction, and visualization used to implement the project’s algorithms.

Project Components

The three required deliverables: (1) a detailed written report, (2) a working image-processing application, and (3) a 10–15-minute presentation and demonstration.