Using gradient model to compare between treatment samples and non-treatment samples

Applications of digital image processing are mostly in the area of medical, plants laboratory, in the surgery images, Cameras, Video, Electro-photographic and Television images for improving the quality of images and code system. The scanning electron microscope (SEM) is the most acceptable tool being used for bio-measurements and in this paper we have designed the Gradient model to help us detecting and comparing between treatment samples and non-treatment samples in bacteria samples. The error probability of discussion becomes high due to poor information occurrence of some natural properties. We have addressed this issue in our paper by using different image processing technique in order to get more clarity and sufficiency of information. This analysis technique is called Gradient model (GD) and the model starts converting two dimensional images of the prepared samples to data file (*.dat). This 2D data is subsequently converted to 3D data file by using OpenGL under Visual C++ Language programming which after conversion, finally, can draw up time series charts like histogram; and traces management contours; and 3D surface to carry out image analysis. This analysis is of vital importance and can help in comparing between the treatment of bacterial samples and non-treatment samples. Instead of carryout full analysis again and again, this method facilitates partial analysis of any part of any randomly selected image and can accommodate different sizes of the images as well. This property and functionality of the model ensures more accuracy of the analysis and reduces the cost of hardware used.