scholarly journals Gray-Level Histogram based Multilevel Threshold Selection with Bat Algorithm

2014 ◽  
Vol 93 (16) ◽  
pp. 1-8 ◽  
Author(s):  
V. Rajinikanth ◽  
J. P. Aashiha ◽  
A. Atchaya
Keyword(s):  
Bat Algorithm ◽  
Gray Level ◽  
Threshold Selection ◽  
Gray Level Histogram

CONNECTIONIST MODEL BINARIZATION

1991 ◽  
Vol 05 (04) ◽  
pp. 629-644 ◽  
Author(s):  
NOBORU BABAGUCHI ◽  
KOJI YAMADA ◽  
KOICHI KISE ◽  
YOSHIKAZU TEZUKA
Keyword(s):  
Back Propagation ◽  
Connectionist Model ◽  
Gray Level ◽  
Threshold Selection ◽  
Back Propagation Algorithm ◽  
Image Binarization ◽  
Multilayer Network ◽  
Binarization Method ◽  
Gray Level Histogram ◽  
Binarized Image

Image binarization is a task to convert gray-level images into bi-level ones. Its underlying notion can be simply thought of as threshold selection. However, the result of binarization will cause significant influence on the process of image recognition or understanding. In this paper we discuss a new binarization method, named CMB (connectionist model binarization), which uses the connectionist model. In the method a gray-level histogram is input to a multilayer network trained with the back-propagation algorithm to obtain a threshold which gives a visually suitable binarized image. From the experimental results, it was verified that CMB is an effective binarization method in comparison with other methods.

Ultrasonic Tissue Characterization with Gray Level Histogram Width

2013 ◽  
pp. 17-17
Author(s):  
Kazuo Maeda ◽  
Masaji Utsu ◽  
Nobuhiro Yamamoto ◽  
Mariko Serizawa
Keyword(s):  
Tissue Characterization ◽  
Gray Level ◽  
Gray Level Histogram

A novel method for evaluating uterine cervical consistency using vaginal ultrasound gray-level histogram

2010 ◽  
Vol 38 (5) ◽  
Author(s):  
Tomoyuki Kuwata ◽  
Shigeki Matsubara ◽  
Nobuyuki Taniguchi ◽  
Akihide Ohkuchi ◽  
Takashi Ohkusa ◽  
...  
Keyword(s):  
Gray Level ◽  
Vaginal Ultrasound ◽  
Novel Method ◽  
Gray Level Histogram

MRI intensity nonuniformity correction using simultaneously spatial and gray-level histogram information

2007 ◽  
Vol 31 (2) ◽  
pp. 81-90 ◽  
Author(s):  
Julien Milles ◽  
Yue Min Zhu ◽  
Gérard Gimenez ◽  
Charles R.G. Guttmann ◽  
Isabelle E. Magnin
Keyword(s):  
Gray Level ◽  
Nonuniformity Correction ◽  
Intensity Nonuniformity ◽  
Gray Level Histogram

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.

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