Edge Detection of Turbid Bacterial Liquid Microscopic Images Based on a Modified Canny Algorithm
The edge detection of low-resolution images taken from turbid bacterial liquid is a confusing problem in the seg-mentation and recognition of microscopic images.In traditional Canny algorithm,there are some problems in edge detection,such as excessive image smoothing,manual determination of threshold,high error rate and missed judgment.This paper presents an im-proved Canny algorithm.In this paper,the bilateral filter instead of Gaussian filter for preprocessing is used to preserve the edge and remove the noise.The gradient template in 45°and 135°directions is added to calculate the gradient amplitude.Linear interpo-lation is used to improve non-maximum suppression,which enhances the accuracy of edge detection.Threshold selection is changed from manual selection to 3×3 window mean automatic generation threshold,which enhances the adaptability.The edges are connected by the recursive boundary tracking method.The algorithm is verified by high contrast and low contrast microscopic imag-es.The results show that improved Canny algorithm is better than traditional algorithm.This algorithm can accurately extract the edge of the microscopic image of turbid sample cells,which is significate for the subsequent cell microscopic image segmentation and recognition.
microscopic imagebilateral filteringadaptive thresholdlocal mean
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