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very important feature extraction method that is commonly used in computer visions and image processing applications is counting of objects. This paper represents a modified sequential region labeling algorithm which counts the homogeneous region of different objects on image. It is based on 4-connected, 6-connected and 8-connected component technique. These algorithms scan the image pixel by pixel from left to right and top to bottom sequentially and assign a label to every foreground pixels in binary image. Salt and pepper noise is usually prevalent in such images. Removing this noise is an important issue. We propose median filter algorithm to removed such type of noise and obtain better results. This technique may be applied to uniform, non- uniform, regular, irregular objects with different shape, size and file formats. Binary images are obtained from color or greyscale images by proper thresholding. In this proposed method, the regions of various objects are found by region labelling process. These distinct regions are given the number of objects that are present inside the image. This algorithm is implemented on the .net technology. These methods produced good performance in term of accuracy. This is a process oriented task. So the machine having higher processing speed can serve the purpose better.

Counting Objects using Homogeneous Connected Components