Due to its small unit size, dense array, weak fluorescence signal, and vulnerability to light dis. tribution, it is difficult to locate the sample points of honeycomb stacked digital PCR microarray images. In this paper, an algorithm of three-channel honeycomb fluorescence spots addressing based on morpholo. gy, and a digital PCR image information extraction method are proposed, which can quickly and effective. ly identify the weak fluorescence information of biomolecules in microarray chips. The image registration fusion is carried out for different channels to make the sample points orderly. Select effective spots area by enhancing the contrast of the image. Use improved gamma algorithm to remove uneven distribution of illu. mination. Identify, locate and segment the closely arranged spots on the microarray chip based on morpho. logical algorithm, and then, extract the fluorescence information of biomolecules of each spot. Using this method, the image processing time of a digital PCR chip with about 20 000 microcells is less than 20 s. Compared with the existing spot addressing methods, the processing time of the same number of samples can be reduced by three orders of magnitude. Compared with the results of standard instruments, the accu. racy of sample recognition is 98. 79%, and the accuracy of biological information calculation(copy num. ber)is 96. 2%. In this paper, the three-way honeycomb fluorescence spot addressing algorithm and digital PCR image information extraction method based on morphology are proposed to overcome the difficulty of locating the spots in the honeycomb stacked microarray fluorescence picture. Compared with the existing methods, biological information can be obtained quickly and accurately, which lays a foundation for pre. cise quantification of digital PCR technology.