New Segmentation Scheme for Low Quality Fingerprint Images

2015 ◽  
Vol 742 ◽  
pp. 272-276 ◽  
Author(s):  
Bo Guo ◽  
Bo Han ◽  
Lei Niu
Keyword(s):  
Image Segmentation ◽  
Fingerprint Image ◽  
Fingerprint Segmentation ◽  
Better Than

Proposes a new scheme for low quality fingerprint images which is used point oriental image and based on gray distributing rule of the pixels after investigating existing approaches to fingerprint segmentation. Experiment results indicated that this scheme performs better than traditional fingerprint image segmentation alogrithms. And it has higher performance in terms of efficiency and robustness.

Fingerprint Segmentation Based on Fractal Dimension

2012 ◽  
Vol 433-440 ◽  
pp. 421-425
Author(s):  
Hui Li ◽  
Pei Zhuo Liu ◽  
Rong Bo He ◽  
Yuan Yuan Yang
Keyword(s):  
Fractal Dimension ◽  
Experimental Results ◽  
Fingerprint Image ◽  
Image Preprocessing ◽  
New Approach ◽  
Sobel Operator ◽  
Fingerprint Segmentation ◽  
Better Than

Fingerprint segmentation is an important problem in fingerprint image preprocessing. This paper describes a new approach to the segmentation of fingerprint images based on fractal dimension. First, the Sobel operator is used to calculate the gradient of fingerprint image, and then we employ the concept of fractal dimension to further analyze the image produced by the first step. By estimating the fractal dimension of the foreground and the background of the fingerprint, and combining grayscale as features, finally accomplish the segmentation of fingerprint. The experimental results show that the proposed method performs well in fingerprint segmenting and is better than the existing method.

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 Gradient Based Approach for Fingerprint Image Segmentation using Morphological Operators

2018 ◽  
Vol 7 (4) ◽  
pp. 2453
Author(s):  
Reji Joy ◽  
Hemalatha S
Keyword(s):  
Image Segmentation ◽  
Individual Recognition ◽  
Input Image ◽  
Fingerprint Recognition ◽  
Identification System ◽  
Morphological Operations ◽  
Fingerprint Image ◽  
Segmentation Process ◽  
Gradient Based ◽  
Fingerprint Segmentation

The advancement of science and technology has made the reliable individual recognition and identification systems to become very popular. From the various biometric characteristics, fingerprint is one of the popular method because of its easiness and not much effort is required to acquire fingerprint. First step for an Automated Fingerprint Identification System (AFIS) is the segmentation of fingerprint from the acquired image. During fingerprint segmentation process the input image is decomposed into foreground and background areas. The foreground area contains information that are needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false features. So in an AFIS, fingerprint image segmentation plays an important role in carefully separating ridge like part (foreground) from noisy background. Gradient based method is commonly used for segmentation process. Since gradient estimation is erroneous in noisy images, the study proposes a combination of gradient mask and morphological operations to segment fingerprint foreground effectively. The results obtained prove that the new method is suited for fingerprint segmentation.

Moth-Flame Optimization Algorithm Based Multilevel Thresholding for Image Segmentation

2017 ◽  
Vol 8 (4) ◽  
pp. 58-83 ◽  
Author(s):  
Abdul Kayom Md Khairuzzaman ◽  
Saurabh Chaudhury
Keyword(s):  
Image Segmentation ◽  
Computational Complexity ◽  
Signal To Noise Ratio ◽  
Fitness Function ◽  
Multilevel Thresholding ◽  
Bacterial Foraging Optimization ◽  
Kapur’S Entropy ◽  
Moth Flame Optimization Algorithm ◽  
Popular Image ◽  
Better Than

Multilevel thresholding is a popular image segmentation technique. However, computational complexity of multilevel thresholding increases very rapidly with increasing number of thresholds. Metaheuristic algorithms are applied to reduce computational complexity of multilevel thresholding. A new method of multilevel thresholding based on Moth-Flame Optimization (MFO) algorithm is proposed in this paper. The goodness of the thresholds is evaluated using Kapur's entropy or Otsu's between class variance function. The proposed method is tested on a set of benchmark test images and the performance is compared with PSO (Particle Swarm Optimization) and BFO (Bacterial Foraging Optimization) based methods. The results are analyzed objectively using the fitness function and the Peak Signal to Noise Ratio (PSNR) values. It is found that MFO based multilevel thresholding method performs better than the PSO and BFO based methods.

scholarly journals Filter Design and Performance Evaluation for Fingerprint Image Segmentation

PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0154160 ◽  
Author(s):  
Duy Hoang Thai ◽  
Stephan Huckemann ◽  
Carsten Gottschlich
Keyword(s):  
Image Segmentation ◽  
Performance Evaluation ◽  
Filter Design ◽  
Fingerprint Image ◽  
And Performance

scholarly journals Modified JSEG algorithm for reducing over-segmentation problems in underwater coral reef images

2019 ◽  
Vol 9 (6) ◽  
pp. 5244
Author(s):  
Mohammad Sameer Aloun ◽  
Muhammad Suzuri Hitam ◽  
Wan NuralJawahir Hj Wan Yussof ◽  
Abdul Aziz K Abdul Hamid ◽  
Zainuddin Bachok
Keyword(s):  
Image Segmentation ◽  
Coral Reef ◽  
Texture Features ◽  
Color Histogram ◽  
Similarity Measurement ◽  
Segmentation Problem ◽  
Better Than ◽  
Observation Results ◽  
Color And Texture Features

<p>The original JSEG algorithm has proved to be very useful and robust in variety of image segmentation case studies.However, when it is applied into the underwater coral reef images, the original JSEG algorithm produces over-segementation problem, thus making this algorithm futile in such a situation. In this paper, an approach to reduce the over-segmentation problem occurred in the underwater coral reef image segmentation is presented. The approach works by replacing the color histogram computation in region merge stage of the original JSEG algorithm with the new computation of color and texture features in the similarity measurement. Based on the perceptual observation results of the test images, the proposed modified JSEG algorithm could automatically segment the regions better than the original JSEG algorithm.</p>

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