A method for counting round-like particle targets based on machine vision

Abstract

The invention discloses a method for counting round-like particle targets based on machine vision. The counting method first carries out image acquisition, then performs image enhancement preprocessing and extracts the extended edge features of the round particles, then reconstructs the round particle features according to the extracted extended edge features, and finally performs the round-like particle feature segmentation and noise elimination, Finally, the counting of round-like particle targets is realized. Based on the extended edge feature information between round-like particles, this method uses a feature reconstruction method to reconstruct the characteristics of round-like particles, so as to realize fast and accurate segmentation and counting of round-like particles; the counting algorithm has high efficiency, good robustness, The accuracy rate is high, which can meet the real-time requirements of the production line, improve the automation level of the production line, and have practical application value.

Description

technical field [0001] The invention belongs to the technical field of machine vision and pattern recognition, in particular to a method for counting round-like particle targets based on feature reconstruction in machine vision and image features. Background technique [0002] The image analysis and processing technology of quasi-round particles is an important research content in the field of computer vision applications. It has a wide range of application requirements in different fields such as medical health, agricultural product processing, and industrial production, such as: packaging counting of agricultural products such as apples and eggs, Counting of industrial production such as rods and mouth rods, early detection and analysis of the number and shape of cell particles in various microscopic images for diagnosis of major diseases. These round particles have characteristic information such as close arrangement, similar texture and grayscale characteristics, and the...

AI Technical Summary

Problems solved by technology

However, the particle target segmentation based on the edge analysis method cannot solve the following problems well: ①The shapes of the stacked particles are different, and the separation points at the interconnections are not clear; ②The squeezed edge of the particle target is not smooth and irregular The separation points are prone to noise interference; ③The contrast between the stacked particle regions is very small or even non-existent; ④The algorithm is complex and the scope of application is limited, so it is not suitable for large-scale industrial production applications

However, there are two problems in the segmentation method based on morphology: ① When the particles are stacked and squeezed severely, the adhesion will shrink unevenly, making it difficult to segment the stacked area into independent target nuclei even after several times of erosion; ② Corrosion Dilation and dilation are not reciprocal operators. Even after the same number of erosion and dilation operations, the original image cannot be guaranteed to be completely restored, resulting in segmentation errors.

Images