Computational methods for the segmentation of images of objects from background in a flow imaging instrument

摘要

In automated computation-based interpretation of images, the accuracy and reliability of the detection and delineation of objects, known as “object segmentation,” is implemented so as to provide efficient performance. In a multi-step process, objects are first detected and captured into regions of interest (ROIs). Sets of pixels belonging to respective objects are then identified. Preferably object detection is achieved using both a two-dimensional (2D) low pass filter and a 2D edge enhancement filter. Two different gradient based edge enhancement filters are disclosed. One embodiment of the invention defines a (ROI) by first determining the center of objects by executing a plurality of decimations on the filtered image data, and then establishing object boundaries. In a second embodiment the ROI is defined by generating an amplitude histogram of the filtered image data, and for histograms exceeding a threshold determining by pixel which rows are to be included in the ROI.