A novel method for compressing color images using binary image segmentation and contour polygons

2004 ◽  
Author(s):  
A. Nabout ◽  
B. Tibken
Keyword(s):  
Image Segmentation ◽  
Color Images ◽  
Binary Image ◽  
Novel Method

A Novel Neutrosophic Image Segmentation Based on Improved Fuzzy C-Means Algorithm (NIS-IFCM)

2019 ◽  
Vol 34 (05) ◽  
pp. 2055011
Author(s):  
Jing Zhao ◽  
Xiaoli Wang ◽  
Ming Li
Keyword(s):  
Computer Vision ◽  
Particle Swarm Optimization ◽  
Image Segmentation ◽  
Classical Problem ◽  
Local Optimum ◽  
The Novel ◽  
Swarm Optimization ◽  
Novel Method ◽  
Fuzzy C Means Algorithm ◽  
Novel Algorithm

Image segmentation is a classical problem in the field of computer vision. Fuzzy [Formula: see text]-means algorithm (FCM) is often used in image segmentation. However, when there is noise in the image, it easily falls into the local optimum, which results in poor image boundary segmentation effect. A novel method is proposed to solve this problem. In the proposed method, first, the image is transformed into a neutrosophic image. In order to improve the ability of global search, a combined FCM based on particle swarm optimization (PSO) is proposed. Finally, the proposed algorithm is applied to the neutrosophic image segmentation. The results of experiments show that the novel algorithm can eliminate image noise more effectively than the FCM algorithm, and make the boundary of the segmentation area clearer.

Estimation of Fractal Dimension in Different Color Model

2018 ◽  
Vol 8 (1) ◽  
pp. 75-93
Author(s):  
Sumitra Kisan ◽  
Sarojananda Mishra ◽  
Ajay Chawda ◽  
Sanjay Nayak
Keyword(s):  
Fractal Dimension ◽  
Color Space ◽  
Vital Role ◽  
Color Images ◽  
Color Spaces ◽  
Fractal Surfaces ◽  
Test Operation ◽  
Novel Method ◽  
Rgb Color Space ◽  
Different Color

This article describes how the term fractal dimension (FD) plays a vital role in fractal geometry. It is a degree that distinguishes the complexity and the irregularity of fractals, denoting the amount of space filled up. There are many procedures to evaluate the dimension for fractal surfaces, like box count, differential box count, and the improved differential box count method. These methods are basically used for grey scale images. The authors' objective in this article is to estimate the fractal dimension of color images using different color models. The authors have proposed a novel method for the estimation in CMY and HSV color spaces. In order to achieve the result, they performed test operation by taking number of color images in RGB color space. The authors have presented their experimental results and discussed the issues that characterize the approach. At the end, the authors have concluded the article with the analysis of calculated FDs for images with different color space.

A Novel Method for Fingerprint Image Segmentation Based on Adaptative Gabor Filters

2017 ◽  
Author(s):  
J.J. Brasileiro ◽  
R.C. Ramos ◽  
I.L.P. Andrezza ◽  
R.L. Parente ◽  
H.M. Gomes ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Gabor Filters ◽  
Fingerprint Image ◽  
Novel Method

scholarly journals Detection of Surface Defects on Steel Strips Based on Singular Value Decomposition of Digital Image

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Qianlai Sun ◽  
Jianghui Cai ◽  
Zhiyi Sun
Keyword(s):  
Image Segmentation ◽  
Singular Value Decomposition ◽  
Digital Image ◽  
Manufacturing Industry ◽  
Surface Defects ◽  
Sudden Change ◽  
Singular Value ◽  
Steel Strips ◽  
Novel Method ◽  
Value Decomposition

Image segmentation technology has been widely used to detect the surface defects in metal industries effectively. In some fields of the manufacturing industry, the determination of defects is more concerned than the accurate location and shape of defects. However, most of current image segmentation algorithms are complex or have difficulty determining the defect. This paper presents a novel method for determining and roughly locating the surface defects of steel strips based on Singular Value Decomposition. The method has no need of image segmentation. The gray level matrix of a digital image is projected on its singular vectors obtained by Singular Value Decomposition. A defect is reflected as a sudden change on the projections. Therefore, the defects can be determined and roughly located according to the sudden changes. The experimental results suggest that this method is valid and convenient for determining the surface defects directly.

scholarly journals SAR Image Segmentation Using Morphological Attribute Profiles

2014 ◽  
Vol XL-3 ◽  
pp. 39-44 ◽  
Author(s):  
M. Boldt ◽  
A. Thiele ◽  
K. Schulz ◽  
S. Hinz
Keyword(s):  
Image Segmentation ◽  
High Resolution ◽  
Region Growing ◽  
Object Based Image Analysis ◽  
Sar Image Segmentation ◽  
High Resolution Imagery ◽  
Object Based ◽  
High Resolution Images ◽  
Novel Method ◽  
Image Set

In the last years, the spatial resolution of remote sensing sensors and imagery has continuously improved. Focusing on spaceborne Synthetic Aperture Radar (SAR) sensors, the satellites of the current generation (TerraSAR-X, COSMO-SykMed) are able to acquire images with sub-meter resolution. Indeed, high resolution imagery is visually much better interpretable, but most of the established pixel-based analysis methods have become more or less impracticable since, in high resolution images, self-sufficient objects (vehicle, building) are represented by a large number of pixels. Methods dealing with Object-Based Image Analysis (OBIA) provide help. Objects (segments) are groupings of pixels resulting from image segmentation algorithms based on homogeneity criteria. The image set is represented by image segments, which allows the development of rule-based analysis schemes. For example, segments can be described or categorized by their local neighborhood in a context-based manner. <br><br> In this paper, a novel method for the segmentation of high resolution SAR images is presented. It is based on the calculation of morphological differential attribute profiles (DAP) which are analyzed pixel-wise in a region growing procedure. The method distinguishes between heterogeneous and homogeneous image content and delivers a precise segmentation result.

The Study of Forest Fire Color Image Segmentation

2011 ◽  
Vol 474-476 ◽  
pp. 2140-2145
Author(s):  
Si Li ◽  
Hong E Ren
Keyword(s):  
Image Segmentation ◽  
Forest Fire ◽  
Color Image ◽  
Color Space ◽  
Color Images ◽  
Color Image Segmentation ◽  
Hsv Color Space ◽  
Segmentation Methods ◽  
Time Periods ◽  
Night And Day

Combined with the composition characteristics of forest fire image background when the forest fire occurred during different time periods of night and day, different image segmentation methods were applied to the forest fire color images of different time periods respectively, which could improve the efficiency of image processing. Meanwhile, application of H and S components from HSV color space, the strategy on color image segmentation which processed the segmentation processing to forest fire color images with complicated background was proposed combined with Otsu algorithm. The results of simulation experiment showed that the above-mentioned segmentation methods were obtained satisfactory segmentation effects when the segmentation on forest fire color images during different time periods of night and day were processed respectively. And also application of Otsu algorithm based on HSV color model, the forest fire image segmentation occurred in the daytime was processed, which overcame the interference factors of light and smoke, as well as the shortage of noise sensibility due to Otsu algorithm.

Character Detection and String Identification on a Signboard in Scene Image Based on Criterions of Segmented Images

2011 ◽  
Vol 103 ◽  
pp. 658-666
Author(s):  
Hideaki Kawano ◽  
Hideaki Orii ◽  
Hiroshi Maeda
Keyword(s):  
Image Segmentation ◽  
Binary Image ◽  
Color Information ◽  
Binary Images ◽  
Input Interface ◽  
Scene Image ◽  
Segmented Images

In this paper, a method which specifies the signboard region and extracts the charactersinside the signboard is proposed.We usually take notes not to forget what we should leave to memory.But it is often that the task is too troublesome. Our aim is the development of a new input-interface soas to input texts froma picture.Most of signboards are composed of almostmonochromatic region. Onthe basis of this observation, image segmentation using color information is applied, and then we getsome binary images by applying threshold for each segmented region. Each binary image is enclosedby the smallest circumscribed square. The signboard region is specified according to distribution andarea of the white pixels inside the square. As a result of experiment, we confirmed the effectivenessof the proposed method.

scholarly journals A Novel Method for Grayscale Image Segmentation by Using GIT-PCANN

2011 ◽  
Vol 3 (5) ◽  
pp. 12-18
Author(s):  
Haiyan Li ◽  
Lei Guo ◽  
Yufeng Zhang ◽  
Xinling Shi ◽  
Jianhua Chen
Keyword(s):  
Image Segmentation ◽  
Grayscale Image ◽  
Novel Method
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