Project name: Blob Counting Application
Course: CS135 - Visual Programming
Authors:
Jade Kenneth S. Darunday (2018)
Kim S. Escabarte (2018)
John Christopher A. Go (2018)
Mikhail M. Lumanta (2018)

Abstract:
This study reviews about counting of objects in an image using the selected image processing techniques also known as blob counting. Counting is one of the most common action performed by people. The objective of this study is to be able to gather information on how blob counting can make counting objects easier using some selected image processing techniques. These image processing techniques are: grayscale which is used in removing unnecessary color information aside from gray in an image, threshold which is used in separating the colors between black and white using its threshold value, dilation which is used to split the black objects from white objects in a threshold image and erosion which is used in removing noises from a threshold image. There are also three methods of blob counting used in this study. These methods are Grassfire, Horizontal Layered Scanning and Blob Counting Using Template Matching.