In this paper two image processing algorithms are presented for small object detection purpose which can be used in blob analysis of sprayer calibration and other similar applications. The algorithms named label injection (LI) and color injection (CI) respectively. In the latter an object is detected and counted by applying a sequential color code, thus at the end of processing each object (blob) will be distinguished with a unique color and in the former this is carried out by applying a unique numerical code to each object. The algorithms have been implemented and adapted in a program called Scientific Image Blob Analysis (SIBA). The program can read the scanned image of water sensitive cards, obtained from nozzle\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s spray. Some threshold techniques are also used for noise removal and converting the original image to a binary one (e.g. red for blob and white for background). The blob features calculated in the program are area, actual diameter, Number Median Diameter (NMD), Volume Median Diameter (VMD), blob density (Number of blobs/area), and percentage of blob\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s area coverage, blob count and finally the uniformity of spray (standard deviation of droplet\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s size).The algorithms were evaluated analytically and experimentally, comparing with the results of a leaf area meter and a planimeter. Although the results showed a more accurate and faster performance for both algorithms, a direct correlation was also found between their accuracy and the image\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s resolution. In other words, the higher the resolution of the image, the more accurate of the results particularly for the smaller blobs. This was mainly due to the steplike inherent of the pixels showing a blob\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s boundary. However, by choosing an appropriate resolution the error of measurement may reduce to %1. The program can also easily be used for any area detection and calculation of the images such as leaf, fruits,beans etc. It is a good package especially for the researchers in the developing countries with a limit access to similar resources. Moreover there might be some uncertainty about the accuracy of such commercial products.

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