A novel method for detecting and counting overlapping tracks in SSNTD by image processing techniques

• A new method is introduced to recognize nuclear tracks by image processing.
• The method is used to specify neighborhood pixels in junction points in overlapping tracks.
• Enhanced method of counting overlapping tracks.
• New counting system has linear behavior in counting tracks with density less than 300,000 tracks per cm2.
• In the new method, the overlap tracks can be recognized even to 10× tracks and more.

Overlapping object detection and counting is a challenge in image processing. A new method for detecting and counting overlapping circles is presented in this paper. This method is based on pattern recognition and feature extraction using “neighborhood values“ in an object image by implementation of image processing techniques. The junction points are detected by assignment of a value for each pixel in an image. As is shown, the neighborhood values for junction points are larger than the values for other points. This distinction of neighborhood values is the main feature which can be utilized to identify the junction points and to count the overlapping tracks. This method can be used for recognizing and counting charged particle tracks, blood cells and also cancer cells. The method is called “Track Counting based on Neighborhood Values” and is symbolized by “TCNV”.