Semi-automated

This is a plugin bundled with native ImageJ.

See IJ reference for more details > Link

This note presents the design of a scalable software package named ImagePy for analysing biological images. Our contribution is concentrated on facilitating extensibility and interoperability of the software through decoupling the data model from the user interface. Especially with assistance from the Python ecosystem, this software framework makes modern computer algorithms easier to be applied in bioimage analysis.

This method was originally designed to track objects (not necessarily spots) already identified in 2D 
frames and has been applied previously to particle tracking and analysis in high-speed atomic force microscopy image series.

An ImageJ plugin for DEFCoN, the fluorescence spot counter based on fully convolutional neural networks

It implements the template matching function from the OpenCV library. The java interface of OpenCV was done through the javacv library. It is quite similar as the existing template matching plugin but runs much faster and users could choose among six matching methods: 

1.Squared difference

2.Normalized squared difference

3.Cross-correlation

4.Normalized cross-correlation

5.Correlation coefficient

6.Normalized correlation coefficient

The detailed algorithms could be found here.

The cvMatch_Template will search a specific object (image pattern) over an image of interest by the user-specified method.