Finger-Vein Image Enhancement Based on Muti-Threshold Fuzzy Algorithm

2009 ◽  
Author(s):  
Cheng-Bo Yu ◽  
Dong-Mei Zhang ◽  
Hong-Bing Li ◽  
Fang-Fang Zhang
Keyword(s):  
Image Enhancement ◽  
Fuzzy Algorithm ◽  
Finger Vein

scholarly journals Finger-Vein Image Enhancement Using a Fuzzy-Based Fusion Method with Gabor and Retinex Filtering

Sensors ◽  
2014 ◽  
Vol 14 (2) ◽  
pp. 3095-3129 ◽  
Author(s):  
Kwang Shin ◽  
Young Park ◽  
Dat Nguyen ◽  
Kang Park
Keyword(s):  
Image Enhancement ◽  
Fusion Method ◽  
Finger Vein

A New Approach for B Ultrasound Images Enhancement

2013 ◽  
Vol 785-786 ◽  
pp. 1391-1394
Author(s):  
Chun Ying Pang ◽  
Qi Yu Jiao
Keyword(s):  
Clinical Practice ◽  
Image Enhancement ◽  
Ultrasound Images ◽  
Gray Level ◽  
Threshold Selection ◽  
New Approach ◽  
Fuzzy Algorithm ◽  
Enhancement Method

To make B ultrasound images clear, a new image enhancement method was studied.The study used an improved fuzzy algorithm based on gray-level to process B ultrasound images. And the process is largely simple by adding threshold selection which could meet different clinical demand. Several kinds of enhancement algorithms for B ultrasound images are evaluated and compared by using MATLAB to process the same image. The results after contrast show that the improved fuzzy algorithm is effective and achieved in clinical practice.

scholarly journals A Parallel Fuzzy Algorithm for Real-Time Medical Image Enhancement

2020 ◽  
Vol 22 (8) ◽  
pp. 2599-2612
Author(s):  
Josep Arnal ◽  
Mónica Chillarón ◽  
Estíbaliz Parcero ◽  
Luis B. Súcar ◽  
Vicente Vidal
Keyword(s):  
Real Time ◽  
Image Enhancement ◽  
Medical Image ◽  
Fuzzy Algorithm ◽  
Medical Image Enhancement

scholarly journals Finger Vein Segmentation from Infrared Images Based on a Modified Separable Mumford Shah Model and Local Entropy Thresholding

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Marios Vlachos ◽  
Evangelos Dermatas
Keyword(s):  
Image Enhancement ◽  
Local Application ◽  
Local Entropy ◽  
Infrared Images ◽  
Vein Pattern ◽  
Finger Vein ◽  
Small Window ◽  
Minimization Procedure ◽  
Novel Method ◽  
Computationally Intensive

A novel method for finger vein pattern extraction from infrared images is presented. This method involves four steps: preprocessing which performs local normalization of the image intensity, image enhancement, image segmentation, and finally postprocessing for image cleaning. In the image enhancement step, an image which will be both smooth and similar to the original is sought. The enhanced image is obtained by minimizing the objective function of a modified separable Mumford Shah Model. Since, this minimization procedure is computationally intensive for large images, a local application of the Mumford Shah Model in small window neighborhoods is proposed. The finger veins are located in concave nonsmooth regions and, so, in order to distinct them from the other tissue parts, all the differences between the smooth neighborhoods, obtained by the local application of the model, and the corresponding windows of the original image are added. After that, veins in the enhanced image have been sufficiently emphasized. Thus, after image enhancement, an accurate segmentation can be obtained readily by a local entropy thresholding method. Finally, the resulted binary image may suffer from some misclassifications and, so, a postprocessing step is performed in order to extract a robust finger vein pattern.

scholarly journals Finger-Vein Image Enhancement Based on Pulse Coupled Neural Network

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 57226-57237 ◽  
Author(s):  
Lei Lei ◽  
Feng Xi ◽  
Shengyao Chen
Keyword(s):  
Neural Network ◽  
Image Enhancement ◽  
Pulse Coupled Neural Network ◽  
Finger Vein

Remote Sensing Image Enhancement Based on Relative Entropy and Fuzzy Algorithm

2013 ◽  
Vol 13 (13) ◽  
pp. 2394-2398
Author(s):  
Yang Bo ◽  
Jia Zhen-Hong ◽  
Qin Xi-zhong ◽  
Yang Jie ◽  
Hu Ying-jie
Keyword(s):  
Remote Sensing ◽  
Image Enhancement ◽  
Relative Entropy ◽  
Remote Sensing Image ◽  
Fuzzy Algorithm
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