Gene expression analyses by probes of hybridization from mRNA to cDNA targets arrayed on membranes or activated glass surfaces have revolutionized the way of profiling mega level gene expression. The main remaining problems however are sensitivity of detection, reproducibility and data processing. During processing of microarray images, especially irregularities of spot position and shape could generate significant errors. Here we report a novel method to eliminate such obstacles by sensing their edges. Application of morphological gradient technology on separating spots from the background decreases the probability of the errors and gives more accurate information about the states of spots such as the pixel number, degree of fragmentation, width and height of spot, and circumference of spot. Such information can be used for the quality control of cDNA microarray experiments and filtering of low quality spots. In this paper we proposed a method which performing accurate spot segmentation of a microarray image, using morphological gradient image analysis techniques and compared the result with that of conventional methods, which including fixed centre method (using ScanAlyze) and unfixed centre method (using GenePix). The result of the experiment shows that the method presented in this paper is accurate, automatic and robust.