similar cells counting in a digital microscopic image using visualization methods

similar cells counting in a digital microscopic image using visualization methods

the counting problem is estimating the number of objects in the image or video frame that is discussed in the most real-world application, including population monitoring in the monitoring system, the number of wild animals, or the number of trees in an aerial image of the forest. counting cells in microscopy images is also from this issue that aims to estimate the number of cells in the exclusive collection. counting of the sample of one thing in a crowed image is tedious work that often used in biology evaluation from for distance and usually of supervisory data.

our goal is counting the sample of cells in a microscopy image; in this method, when the user marks one point, the system online does learning operation. additionally, this method quickly and carefully can estimate the density of objects with boundary regression. also, we introduced the two methods of visualization for region counting that is very useful and effective. the statics results on microscopic cells illustrated that this system is doing counting operation of five points for initial marking with a 2.66% error rate, for the initial marking, it makes ten points with an average error rate of 0.8%.