scholarly journals Adaptive Fine Distortion Correction Method for Stereo Images of Skin Acquired with a Mobile Phone

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4492
Author(s):  
Cho-I Moon ◽  
Onseok Lee
Keyword(s):  
Mobile Phone ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Skin Surface ◽  
Correction Method ◽  
Distortion Correction ◽  
Stereo Image ◽  
3D Analysis ◽  
Stereo Images ◽  
3D Information

With the development of the mobile phone, we can acquire high-resolution images of the skin to observe its detailed features using a mobile camera. We acquire stereo images using a mobile camera to enable a three-dimensional (3D) analysis of the skin surface. However, geometric changes in the observed skin structure caused by the lens distortion of the mobile phone result in a low accuracy of the 3D information extracted through stereo matching. Therefore, our study proposes a Distortion Correction Matrix (DCM) to correct the fine distortion of close-up mobile images, pixel by pixel. We verified the correction performance by analyzing the results of correspondence point matching in the stereo image corrected using the DCM. We also confirmed the correction results of the image taken at the five different working distances and derived a linear regression model for the relationship between the angle of the image and the distortion ratio. The proposed DCM considers the distortion degree, which appears to be different in the left and right regions of the image. Finally, we performed a fine distortion correction, which is difficult to check with the naked eye. The results of this study can enable the accurate and precise 3D analysis of the skin surface using corrected mobile images.

scholarly journals Comparative Study of the Trueness of the Inner Surface of Crowns Fabricated from Three Types of Lithium Disilicate Blocks

2019 ◽  
Vol 9 (9) ◽  
pp. 1798 ◽  
Author(s):  
Son ◽  
Yu ◽  
Yoon ◽  
Lee
Keyword(s):  
Computer Aided Design ◽  
Three Dimensional ◽  
Lithium Disilicate ◽  
Correction Method ◽  
3D Analysis ◽  
Angular Region ◽  
Second Molar ◽  
Significant Difference ◽  
Inner Surface ◽  
Aided Design

This study set out to compare the three-dimensional (3D) trueness of crowns produced from three types of lithium disilicate blocks. The working model was digitized, and single crowns (maxillary left second molar) were designed using computer-aided design (CAD) software. To produce a crown design model (CDM), a crown design file was extracted from the CAD software. In addition, using the CDM file and a milling machine (N = 20), three types of lithium disilicate blocks (e.max CAD, HASS Rosetta, and VITA Suprinity) were processed. To produce a crown scan model (CSM), the inner surface of each fabricated crown was digitized using a touch-probe scanner. In addition, using 3D inspection software, the CDM was partitioned (into marginal, axis, angular, and occlusal regions), the CDM and CSM were overlapped, and a 3D analysis was conducted. A Kruskal–Wallis test (α = 0.05) was conducted with all-segmented teeth with the root mean square (RMS), and they were analyzed using the Mann–Whitney U-test and the Bonferroni correction method as a post hoc test. There was a significant difference in the trueness of the crowns according to the type of lithium disilicate block (p < 0.001). The overall RMS value was at a maximum for e.max (42.9 ± 4.4 µm), followed by HASS (30.1 ± 9.0 µm) and then VITA (27.3 ± 7.9 µm). However, there was no significant difference between HASS and VITA (p = 0.541). There were significant differences in all regions inside the crown (p < 0.001). There was a significantly high trueness in the angular region inside the crown (p < 0.001). A correction could thus be applied in the CAD process, considering the differences in the trueness by the type of lithium disilicate block. In addition, to attain a crown with an excellent fit, it is necessary to provide a larger setting space for the angular region during the CAD process.

scholarly journals A Survey of Learning Approaches and Application for 3D Vision

2018 ◽  
Vol 173 ◽  
pp. 03053
Author(s):  
Luanhao Lu
Keyword(s):  
Stereo Matching ◽  
Mean Shift ◽  
Three Dimensional ◽  
Image Synthesis ◽  
Learning Approaches ◽  
Median Filtering ◽  
Stereo Images ◽  
Disparity Map ◽  
3D Vision ◽  
2D Images

Three-dimensional (3D) vision extracted from the stereo images or reconstructed from the two-dimensional (2D) images is the most effective topic in computer vision and video surveillance. Three-dimensional scene is constructed through two stereo images which existing disparity map by Stereo vision. Many methods of Stereo matching which contains median filtering, mean-shift segmentation, guided filter and joint trilateral filters [1] are used in many algorithms to construct the precise disparity map. These methods committed to figure out the image synthesis range in different Stereo matching fields and among these techniques cannot perform perfectly every turn. The paper focuses on 3D vision, introduce the background and process of 3D vision, reviews several classical datasets in the field of 3D vision, based on which the learning approaches and several types of applications of 3D vision were evaluated and analyzed.

A Stereo Matching System

2013 ◽  
Vol 5 (2) ◽  
pp. 1-8
Author(s):  
Yingpeng Yang
Keyword(s):  
Stereo Matching ◽  
Learning Algorithm ◽  
Moving Average ◽  
Three Dimensional ◽  
Depth Map ◽  
Stereo Image ◽  
Image Feature ◽  
Matching Algorithm ◽  
Depth Cues ◽  
Computer Vision Technology

Determination of the depth of the image feature distinctive automation and other industries of machine vision and computer vision technology in everyday life are becoming increasingly popular. Some techniques have been proposed to extract from the current depth of a 2D image of the feature, which defines a particular object or structure of the information. In many cases, these techniques are automatic, such as a suitable carrier moving average depth identify objects placed in the 2D image. For this intensive depth cues to solve two stereo matching algorithm using a machine learning algorithm. Other methods, relative to the camera based on the motion of the object have been proposed and analyzed by estimating the optical flow calculation depth map. The method of dense and sparse three-dimensional surface of the object to provide the three-dimensional information. This paper discusses the evaluation of the depth cues, through intensive two standard fast algorithm for real-time stereo image matching algorithm.

ProPaCoL-Net: A Novel Recursive Stereo Image SR Network with Progressive Parallax Coherency Learning

2020 ◽  
Vol 2020 (14) ◽  
pp. 342-1-342-8
Author(s):  
Jeonghun Kim ◽  
Munchurl Kim
Keyword(s):  
Autonomous Vehicles ◽  
Stereo Matching ◽  
Low Cost ◽  
Super Resolution ◽  
Stereo Image ◽  
Stereo Images ◽  
Computationally Efficient ◽  
Stereo Cameras ◽  
Left Image ◽  
Coherency Loss

Recently, stereo cameras have been widely packed in smart phones and autonomous vehicles thanks to low cost and smallsized packages. Nevertheless, acquiring high resolution (HR) stereo images is still a challenging problem. While the traditional stereo image processing tasks have mainly focused on stereo matching, stereo super-resolution (SR) has drawn less attention which is necessitated for HR images. Some deep learning based stereo image SR works have recently shown promising results. However, they have not fully exploited binocular parallax in SR, which may lead to unrealistic visual perception. In this paper, we present a novel and computationally efficient convolutional neural network (CNN) based deep SR network for stereo images by learning parallax coherency between the left and right SR images, which is called ProPaCoL-Net. The proposed ProPaCoL-Net progressively learns parallax coherency via a novel recursive parallax coherency (RPC) module with shared parameters. The RPC module is effectively designed to extract parallax information in prior for the left image SR from its right view input images and vice versa. Furthermore, we propose a parallax coherency loss to reliably train the ProPaCoL-Net. From extensive experiments, the ProPaCoL-Net shows to outperform the very recent state-of-the-art method with average 1.15 dB higher in PSNR.

scholarly journals Disparity Map Generation from Illumination Variant Stereo Images Using Efficient Hierarchical Dynamic Programming

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
Viral H. Borisagar ◽  
Mukesh A. Zaveri
Keyword(s):  
Dynamic Programming ◽  
Stereo Matching ◽  
Stereo Image ◽  
Stereo Pair ◽  
Image Pair ◽  
Stereo Images ◽  
Disparity Map ◽  
Illumination Variation ◽  
Matching Problem ◽  
Wide Range

A novel hierarchical stereo matching algorithm is presented which gives disparity map as output from illumination variant stereo pair. Illumination difference between two stereo images can lead to undesirable output. Stereo image pair often experience illumination variations due to many factors like real and practical situation, spatially and temporally separated camera positions, environmental illumination fluctuation, and the change in the strength or position of the light sources. Window matching and dynamic programming techniques are employed for disparity map estimation. Good quality disparity map is obtained with the optimized path. Homomorphic filtering is used as a preprocessing step to lessen illumination variation between the stereo images. Anisotropic diffusion is used to refine disparity map to give high quality disparity map as a final output. The robust performance of the proposed approach is suitable for real life circumstances where there will be always illumination variation between the images. The matching is carried out in a sequence of images representing the same scene, however in different resolutions. The hierarchical approach adopted decreases the computation time of the stereo matching problem. This algorithm can be helpful in applications like robot navigation, extraction of information from aerial surveys, 3D scene reconstruction, and military and security applications. Similarity measure SAD is often sensitive to illumination variation. It produces unacceptable disparity map results for illumination variant left and right images. Experimental results show that our proposed algorithm produces quality disparity maps for both wide range of illumination variant and invariant stereo image pair.

STEREO MATCHING ALGORITHMS BASED ON FUZZY APPROACH

2002 ◽  
Vol 16 (07) ◽  
pp. 883-899 ◽  
Author(s):  
S. SRINIVAS KUMAR ◽  
B. N. CHATTERJI
Keyword(s):  
Cross Correlation ◽  
Stereo Matching ◽  
Similarity Measures ◽  
Stereo Image ◽  
Image Pair ◽  
Fuzzy Relations ◽  
Stereo Images ◽  
Normalized Cross Correlation ◽  
Fuzzy Aggregation ◽  
The Right

Stereo matching is the central problem of stereovision paradigm. Area-based techniques provide the dense disparity maps and hence they are preferred for stereo correspondence. Normalized cross correlation (NCC), sum of squared differences (SSD) and sum of absolute differences (SAD) are the linear correlation measures generally used in the area-based techniques for stereo matching. In this paper, similarity measure for stereo matching based on fuzzy relations is used to establish the correspondence in the presence of intensity variations in stereo images. The strength of relationship of fuzzified data of two windows in the left image and the right image of stereo image pair is determined by considering the appropriate fuzzy aggregation operators. However, these measures fail to establish correspondence of the pixels in the stereo images in the presence of occluded pixels in the corresponding windows. Another stereo matching algorithm based on fuzzy relations of fuzzy data is used for stereo matching in such regions of images. This algorithm is based on weighted normalized cross correlation (WNCC) of the intensity data in the left and the right windows of stereo image pair. The properties of the similarity measures used in these algorithms are also discussed. Experiments with various real stereo images prove the superiority of these algorithms over normalized cross correlation (NCC) under nonideal conditions.

scholarly journals Ultrahigh Voltage Electron Microscopy Links Neuroanatomy and Neuroscience/Neuroendocrinology

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Hirotaka Sakamoto ◽  
Mitsuhiro Kawata
Keyword(s):  
Electron Microscopy ◽  
Three Dimensional ◽  
Ultrastructural Level ◽  
Biological Research ◽  
3D Analysis ◽  
Small Areas ◽  
Voltage Electron ◽  
Ultrathin Sections ◽  
Chemical Neuroanatomy ◽  
3D Information

The three-dimensional (3D) analysis of anatomical ultrastructures is extremely important in most fields of biological research. Although it is very difficult to perform 3D image analysis on exact serial sets of ultrathin sections, 3D reconstruction from serial ultrathin sections can generally be used to obtain 3D information. However, this technique can only be applied to small areas of a specimen because of technical and physical difficulties. We used ultrahigh voltage electron microscopy (UHVEM) to overcome these difficulties and to study the chemical neuroanatomy of 3D ultrastructures. This methodology, which links UHVEM and light microscopy, is a useful and powerful tool for studying molecular and/or chemical neuroanatomy at the ultrastructural level.

scholarly journals Computer-Assisted Reconstruction and Motion Analysis of the Three-Dimensional Cell

2003 ◽  
Vol 3 ◽  
pp. 827-841 ◽  
Author(s):  
David R. Soll ◽  
Deborah Wessels ◽  
Paul J. Heid ◽  
Edward Voss
Keyword(s):  
3D Reconstruction ◽  
Motion Analysis ◽  
Three Dimensional ◽  
Computer Assisted ◽  
3D Analysis ◽  
Time Intervals ◽  
Abnormal Cells ◽  
3D Information ◽  
Short Time ◽  
Microscopic Techniques

Even though several microscopic techniques provide three-dimensional (3D) information on fixed and living cells, the perception persists that cells are two-dimensional (2D). Cells are, in fact, 3D and their behavior, including the extension of pseudopods, includes an important 3D component. Although treating the cell as a 2D entity has proven effective in understanding how cells locomote, and in identifying defects in a variety of mutant and abnormal cells, there are cases in which 3D reconstruction and analysis are essential. Here, we describe advanced computer-assisted 3D reconstruction and motion analysis programs for both individual live, crawling cells and developing embryos. These systems (3D-DIAS, 3D-DIASemb) can be used to reconstruct and motion analyze at short time intervals the nucleus and pseudopodia as well as the entire surface of a single migrating cell, or every cell and nucleus in a developing embryo. Because all images are converted to mathematical representations, a variety of motility and dynamic morphology parameters can be computed that have proven quite valuable in the identification of mutant behaviors. We also describe examples of mutant behaviors in Dictyostelium that were revealed through 3D analysis.

A Rapid Reserve Inspection Method for Opencast Mine Using Ordinary Digital Camera

2013 ◽  
Vol 333-335 ◽  
pp. 1533-1537
Author(s):  
Biao Yang ◽  
Ming Fei Wu ◽  
Hao Li
Keyword(s):  
Point Cloud ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Digital Camera ◽  
Distortion Correction ◽  
Practical Application ◽  
Design Data ◽  
Inspection Method ◽  
Opencast Mine ◽  
Processing Steps

Reserve inspection is of great significance for rational mining and environmental protection of opencast mine. This paper proposes a method for rapid reserve inspection of opencast mine. The method uses ordinary digital camera which is calibrated rigorously to acquire images of opencast mine, and carries out a series of image processing steps including distortion correction, relative orientation, absolute orientation and stereo matching, thus generating the point cloud and reconstructing the three-dimensional mine model. According to the earlier topographic and design data, the variations of mine surface, volume and reserve are thereby calculated. The practical application of the method proposed has achieved great improvement in efficiency and accuracy for opencast mine reserve inspection.

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