scholarly journals Contour Detection and Completion for Inpainting and Segmentation Based on Topological Gradient and Fast Marching Algorithms

2011 ◽  
Vol 2011 ◽  
pp. 1-20 ◽  
Author(s):  
Didier Auroux ◽  
Laurent D. Cohen ◽  
Mohamed Masmoudi
Keyword(s):  
Image Processing ◽  
Hybrid Algorithm ◽  
Global Analysis ◽  
Image Inpainting ◽  
Contour Detection ◽  
Powerful Method ◽  
Minimal Path ◽  
Fast Marching ◽  
Topological Gradient ◽  
Minimal Path Method

We combine in this paper the topological gradient, which is a powerful method for edge detection in image processing, and a variant of the minimal path method in order to find connected contours. The topological gradient provides a more global analysis of the image than the standard gradient and identifies the main edges of an image. Several image processing problems (e.g., inpainting and segmentation) require continuous contours. For this purpose, we consider the fast marching algorithm in order to find minimal paths in the topological gradient image. This coupled algorithm quickly provides accurate and connected contours. We present then two numerical applications, to image inpainting and segmentation, of this hybrid algorithm.

Implications of Digital Image Processing in the Paraclinical Assessment of the Partially Edentated Patient

2018 ◽  
Vol 69 (2) ◽  
pp. 521-524
Author(s):  
Magda Ecaterina Antohe ◽  
Doriana Agop Forna ◽  
Cristina Gena Dascalu ◽  
Norina Consuela Forna
Keyword(s):  
Image Processing ◽  
Image Enhancement ◽  
Treatment Plan ◽  
Digital Processing ◽  
Contour Detection ◽  
Anatomical Structures ◽  
Imaging Processing ◽  
Point To Point ◽  
Radiological Image ◽  
Processing Techniques

The application of certain digital processing techniques offers the possibility of extra accuracy in the interpretation of paraclinical examinations of this type, with profound implications in the diagnosis as well as in the hierarchy of the treatment plan. The purpose of this study is to identify the type of imaging processing for the identification of pathological elements from orthopantomographies and articular tomographies. A number of 20 orthopantomographies and 15 temporo-mandibular joint tomography have undergone through various image enhancement techniques. Various methods of image enhancement (enhancement) have been used for those procedures whereby it becomes more useful in the following aspects: specific details are highlighted; noise is eliminated; the image becomes more visually attractive. The workings were done in Corel PhotoPaint 7.0, using the automatic procedures available.The choice of a particular type of image enhancement technique has been selected for each type of pathology found in orthopantomographies or articular tomography, providing the best accuracy for an optimal imaging interpretation that underpins a precision diagnosis.Of the most useful imaging processing in the optimization of the orthopantomographic image accuracy the point-to-point transformations are to be noted. The image processing proposed in this article focused primarily on improving the radiological image attributes to highlight specific anatomical structures, and secondly, the contour detection, where it was necessary for the diagnostic purposes as well.

scholarly journals A Projected Forward-Backward Algorithm for Constrained Minimization with Applications to Image Inpainting

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 890
Author(s):  
Suthep Suantai ◽  
Kunrada Kankam ◽  
Prasit Cholamjiak
Keyword(s):  
Image Processing ◽  
Minimization Problem ◽  
Convex Functions ◽  
Lower Semicontinuous ◽  
Image Inpainting ◽  
Constrained Minimization ◽  
Convex Minimization Problem ◽  
Mild Conditions ◽  
Constrained Minimization Problem ◽  
Weak Convergence Theorem

In this research, we study the convex minimization problem in the form of the sum of two proper, lower-semicontinuous, and convex functions. We introduce a new projected forward-backward algorithm using linesearch and inertial techniques. We then establish a weak convergence theorem under mild conditions. It is known that image processing such as inpainting problems can be modeled as the constrained minimization problem of the sum of convex functions. In this connection, we aim to apply the suggested method for solving image inpainting. We also give some comparisons to other methods in the literature. It is shown that the proposed algorithm outperforms others in terms of iterations. Finally, we give an analysis on parameters that are assumed in our hypothesis.

Sperm Flagellum Center-Line Tracing in Fluorescence 3D+t Low SNR Stacks Using an Iterative Minimal Path Method

2017 ◽  
pp. 437-445
Author(s):  
Paul Hernandez-Herrera ◽  
Fernando Montoya ◽  
Juan M. Rendón ◽  
Alberto Darszon ◽  
Gabriel Corkidi
Keyword(s):  
Center Line ◽  
Minimal Path ◽  
Low Snr ◽  
Sperm Flagellum ◽  
Minimal Path Method

scholarly journals An Overview of the Topological Gradient Approach in Image Processing: Advantages and Inconveniences

2010 ◽  
Vol 2010 ◽  
pp. 1-19 ◽  
Author(s):  
Lamia Jaafar Belaid
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Numerical Experiments ◽  
Grey Level ◽  
Major Drawback ◽  
Topological Gradient ◽  
Boundary Measurements ◽  
Topological Asymptotic Expansion ◽  
Gradient Approach ◽  
Segmentation Problem

Image analysis by topological gradient approach is a technique based upon the historic application of the topological asymptotic expansion to crack localization problem from boundary measurements. This paper aims at reviewing this methodology through various applications in image processing; in particular image restoration with edge detection, classification and segmentation problems for both grey level and color images is presented in this work. The numerical experiments show the efficiency of the topological gradient approach for modelling and solving different image analysis problems. However, the topological gradient approach presents a major drawback: the identified edges are not connected and then the results obtained particularly for the segmentation problem can be degraded. To overcome this inconvenience, we propose an alternative solution by combining the topological gradient approach with the watershed technique. The numerical results obtained using the coupled method are very interesting.

scholarly journals A global analysis of urban design types and road transport injury: an image processing study

2020 ◽  
Vol 4 (1) ◽  
pp. e32-e42 ◽  
Author(s):  
Jason Thompson ◽  
Mark Stevenson ◽  
Jasper S Wijnands ◽  
Kerry A Nice ◽  
Gideon DPA Aschwanden ◽  
...  
Keyword(s):  
Image Processing ◽  
Urban Design ◽  
Global Analysis ◽  
Road Transport

scholarly journals High-Resolution Algorithm for Image Segmentation in the Presence of Correlated Noise

2010 ◽  
Vol 2010 ◽  
pp. 1-6
Author(s):  
Haiping Jiang ◽  
Salah Bourennane ◽  
Caroline Fossati
Keyword(s):  
Image Processing ◽  
High Resolution ◽  
Order Statistics ◽  
Second Order ◽  
Contour Detection ◽  
Correlated Noise ◽  
Second Order Statistics ◽  
Multiple Line ◽  
Noise Simulation ◽  
Resolution Algorithm

Multiple line characterization is a most common issue in image processing. A specific formalism turns the contour detection issue of image processing into a source localization issue of array processing. However, the existing methods do not address correlated noise. As a result, the detection performance is degraded. In this paper, we propose to improve the subspace-based high-resolution methods by computing the fourth-order slice cumulant matrix of the received signals instead of second-order statistics, and we estimate contour parameters out of images impaired with correlated Gaussian noise. Simulation results are presented and show that the proposed methods improve line characterization performance compared to second-order statistics.

AN IMAGE INPAINTING ALGORITHM BASED ON ENERGY MINIMIZATION

2012 ◽  
Vol 12 (03) ◽  
pp. 1250017 ◽  
Author(s):  
ZHANJIANG ZHI ◽  
YI SUN
Keyword(s):  
Image Processing ◽  
Energy Minimization ◽  
Image Inpainting ◽  
Research Area ◽  
Local Coordinates ◽  
Essential Idea ◽  
Effective Performance ◽  
Active Research ◽  
Available Information ◽  
Active Research Area

Image inpainting is an active research area in the image processing field. The essential idea of image inpainting algorithm is to fill in the missing or damaged regions with available information from their surroundings. In this paper, we propose two image inpainting models based on the variational method. We show that the diffusion performance of the proposed models for image inpainting are superior to classical total variation (TV) inpainting model according to the physical characteristics in local coordinates. To show the effective performance of the proposed models, we apply it to restoring of scratched photos, text removal and even removal of entire objects from images.

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