Transformation Image into Graphics

Jiang, Xiangqian; Peng, Xiang; Zhang, David

doi:10.1007/1-4020-7775-0_7

Cited by 4 publications

(5 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As mentioned in the Introduction section, once registration is accomplished some redundant data exist in overlapped areas of multiple range images, which should be removed by a following procedure referred to as range-image integration or merging in order to obtain a non-redundant point cloud that represents a true 3D image of object surface. We have developed two different approaches for merging multiple range images: an approach based on mesh stitching [14,15] and approach based on the solution of general iso-surface equation [16], to which interested readers may refer for more technique details.…”

Section: From 25d To Truly 3dmentioning

confidence: 99%

“…Such a geometric representation is a 3D model that represents object surface with a mesh or a parametric surface, and this kind of 3D models can be manipulated such as mesh reduction (to obtain a simplified model) and refinement of a simplified model (see Refs. [14] - [16]) for more details. Fig.…”

Section: Three-dimensional Modeling and Creation Of Photorealistic 3dmentioning

confidence: 99%

See 1 more Smart Citation

Active 3D Imaging Based on White Light Scanning: from Single Sensor to Sensor Networks

Peng¹,

Chen²,

He³

et al. 2017

Proceedings of 3DBODY.TECH 2017 - 8th International Conference and Exhibition On 3D Body Scanning and Processing Technologies,

Self Cite

View full text Add to dashboard Cite

Active 3D imaging based on white light scanning is a sort of efficient techniques which can digitize objects existed in physical world, and therefore to acquire 3D images of test targets. A light coding with a series of structured light patterns, for example, fringe patterns are usually applied for such a 3D imaging modality. A single optical 3D sensor based on fringe projection or 3D optical sensor network composed of multiple node sensors can be regarded as kinds of optical instruments that works on principle of computational imaging. In order to reconstruct a 3D image it is necessary to decode the fringe pattern to get the phase map that acts as special marks encoding each point of test object or scene, resulting in accurate determination of point correspondence. Once the homologous pairs identified precisely a 3D image can be obtained through a series of computations using a stereoscopic vision theory. This paper will briefly reviewed the working principle of an optical digitizer based on the strategy of phase-aided active imaging (PAAI) and that of 3D sensor network composed of multiple PAAI sensors. In addition, many potential applications in 3D body scanning, face scanning, and heritage digitizing will also be addressed in this paper to show great potentials of 3D optical digitizer based on the PAAI strategy and PAAI-based optical measurement network. Both academic research at the Shenzhen University and commercialized products developed at the Shenzhen ESUN Co. Ltd. with number of patented technologies will be presented.

show abstract

Section: From 25d To Truly 3dmentioning

confidence: 99%

Section: Three-dimensional Modeling and Creation Of Photorealistic 3dmentioning

confidence: 99%

Active 3D Imaging Based on White Light Scanning: from Single Sensor to Sensor Networks

Peng¹,

Chen²,

He³

et al. 2017

Proceedings of 3DBODY.TECH 2017 - 8th International Conference and Exhibition On 3D Body Scanning and Processing Technologies,

Self Cite

View full text Add to dashboard Cite

show abstract

“…An important issue is how to manage the fusion of data in the overlapped region. In our approach, the integration of multiple range images has been accomplished by a stitchingbased technique [13]. The integration of multiple range images can be symbolically described as follows:…”

Section: B Registration and Integration Of Multiple Range Imagesmentioning

confidence: 99%

“…Those partial range images with overlapped regions will then be registered in a common coordinate system [11,12]. Furthermore, another procedure, referred to as the integration of multiple range images, is also required to remove the redundant data in overlapped regions in a unified frame, resulting in a complete and nonredundant point cloud [13][14][15]. Once the point cloud depicting the object surface is established, various geometric representations such as a triangular mesh, a B-spline surface, an implicit surface, and a subdivision surface could be utilized to represent a geometric model of a real-life object [15].…”

Section: Introductionmentioning

confidence: 99%

Generation of photorealistic 3D image using optical digitizer

Liu¹,

Peng²,

Yin

et al. 2012

Appl. Opt.

View full text Add to dashboard Cite

A technique to generate a photorealistic three-dimensional (3D) image and color-textured model using a dedicated optical digitizer is presented. The proposed technique is started with the range and texture image acquisition from different viewpoints, followed by the registration and integration of multiple range images to get a complete and nonredundant point cloud that represents a real-life object. The accuracy of the range image and the precision of correspondence between the range image and texture image are guaranteed by sensor system calibration. Based on the point cloud, a geometric model is established by considering the connectivity of adjacent range image points. In order to enhance the photorealistic effect, we suggest a texture blending technique that utilizes a composite-weight strategy to blend the texture images within the overlapped region. This technique allows more efficient removal of the artifacts existing in the registered texture image, leading to a 3D image with photorealistic quality and color-texture modeling. Experimental results are also presented to testify to the validity of the proposed method.

show abstract

“…Range image acquisition techniques can be divided into two broad categories: passive methods and active methods. Passive methods do not interact with the object, whereas active methods do, making contact with the object or projecting some kind of energy onto the surface of the object [18]. Optical triangulation is one of the most popular approaches for data acquisition.…”

Section: Generation Of 3-d Mesh Surfacementioning

confidence: 99%

Feature Detection of an Object by Image Fusion

Pati¹,

Dutta²,

Barua³

2010

IJCA

View full text Add to dashboard Cite

In this paper, we propose a novel method for feature detection of an object by fusion of range and intensity images. For this purpose, we have developed a data acquisition system with a laser source and camera interfaced with Silicon Graphics machine. 3-D mesh representation of the surface of the object is obtained from the acquired range images. Extraction of structural features from the range images has been performed by two methods i.e. coordinate thresholding technique and Laplacian of Gaussian (LoG) edge detector. Extraction of structural features from the intensity image of the object has been performed by the Hough transform technique and Canny edge detector. An approach using shape signatures has been proposed to detect corner points in the edge maps obtained using LoG detector as well as Canny detector. The extracted 3-D edge maps as well as the detected corner points have been mapped to 2-D plane. The methodology for manual fusion of edge maps with the help of affine transformation and the concept of automatic fusion of edge maps by affine transformation followed by iterative closest point (ICP) algorithm have been introduced in this work. The automated technique for fusion overcomes the drawbacks associated with manual fusion. The fusion algorithm provides a composite image with more accurate and reliable information about the important features of the object.

show abstract

Transformation Image into Graphics

Cited by 4 publications

References 48 publications

Active 3D Imaging Based on White Light Scanning: from Single Sensor to Sensor Networks

Active 3D Imaging Based on White Light Scanning: from Single Sensor to Sensor Networks

Generation of photorealistic 3D image using optical digitizer

Feature Detection of an Object by Image Fusion

Contact Info

Product

Resources

About