A novel approach of K-means based fingerprint segmentation algorithm

2012 ◽  
Author(s):  
Huina Li ◽  
Yuan Ping
Keyword(s):  
Segmentation Algorithm ◽  
Novel Approach ◽  
Fingerprint Segmentation

Analyses and System Implement to Fingerprint Image Segmentation Algorithm Based on Field

2010 ◽  
Vol 159 ◽  
pp. 291-296
Author(s):  
Yan Bai Wang ◽  
Lu Tan ◽  
Nian Feng Li ◽  
Wei Liu
Keyword(s):  
Image Segmentation ◽  
Separation Zone ◽  
Experimental System ◽  
Segmentation Algorithm ◽  
Experimental Results ◽  
Gradient Field ◽  
Fingerprint Image ◽  
Fingerprint Segmentation ◽  
Image Segmentation Algorithm

Introduced the fingerprint segmentation algorithm based on strength field and gradient field and designed the experimental system for the algorithm. The method is used to carry on the massive tests with fingerprint images by APC fingerprint gathering. The experimental results show that this method achieved a good fingerprint image foreground and background separation zone.

scholarly journals A proposal to measure the similarity between retinal vessel segmentations images

Nova Scientia ◽  
2019 ◽  
Vol 11 (22) ◽  
pp. 224-245 ◽  
Author(s):  
Marco A. Escobar ◽  
José R. Guzmán Sepúlveda ◽  
Jorge R. Parra Michel ◽  
Rafael Guzmán Cabrera
Keyword(s):  
Fractal Dimension ◽  
Structural Properties ◽  
Strong Correlation ◽  
Performance Metrics ◽  
Automatic Segmentation ◽  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Segmentation Algorithm ◽  
Novel Approach ◽  
Retinal Vessel Segmentation

Introduction: We propose a novel approach for the assessment of the similarity of retinal vessel segmentation images that is based on linking the standard performance metrics of a segmentation algorithm, with the actual structural properties of the images through the fractal dimension.Method: We apply our methodology to compare the vascularity extracted by automatic segmentation against manually segmented images.Results: We demonstrate that the strong correlation between the standard metrics and fractal dimension is preserved regardless of the size of the subimages analyzed.Discussion or Conclusion: We show that the fractal dimension is correlated to the segmentation algorithm’s performance and therefore it can be used as a comparison metric.

GLCM Inspired Fingerprints Segmentation Algorithm with Adaptive Block Size

2012 ◽  
Vol 239-240 ◽  
pp. 1456-1461
Author(s):  
Hui Na Li ◽  
Jun Li Luo
Keyword(s):  
Block Size ◽  
Segmentation Algorithm ◽  
Experimental Results ◽  
Gray Level ◽  
Fingerprint Image ◽  
Pixel Pair ◽  
Fingerprint Segmentation ◽  
The Mean ◽  
Occurrence Matrix ◽  
Self Adaptive

In order to reduce the dependence on the images' sizes, resolutions and qualities, a self-adaptive block size fingerprint segmentation algorithm based on the gray level co-occurrence matrix (GLCM) is proposed. Firstly, the image is divided into a number of non-overlapped rectangular blocks whose size is automatically determined by the mean of the ridge distance from the spectrogram. Then the contrasts of the GLCM of each block in different directions of pixel-pair could be calculated. Since the variances of these contrasts are different for the foreground and the background, finally, the fingerprint image can be segmented correctly. Experimental results show that the proposed algorithm performs effectively in processing images gathered by various fingerprint sensors in diverse environments.

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