BibTex RIS Kaynak Göster

Obtaining Three Dimensional Point Clouds from the Digital Images of Rectangular Prism Shaped Objects

Yıl 2012, Cilt: 2 Sayı: 2, 160 - 170, 31.12.2012

Öz

Kaynakça

  • As the number of points in point clouds which are obtained for the object is too much,
  • approximately 1-4 million, in the marked image to obtain its solid model needs some time,
  • In image processing which is done pixel to pixel according to the color analysis, color loss in the
  • image cause regional point loss, which causes some problems to model the part,
  • If the size of the object in the image and processed image is big, the size of the obtained point
  • cloud file becomes big.
  • It is aimed to obtain three dimensional point clouds for circular, curved and complex forms of objects in further studies.
  • Azuma, R., (1995). A survey of augmented reality. Computer Graphics SIGGRAPH Proc., 1-38.
  • Barbero B.R. and Ureta, E.S. (2011). Comparative study of different digitization techniques and their accuracy. Comp. Aided Design, 43, 188-206.
  • Benlamri, R. and Al-Marzooqi, Y. (2004). Free-from object segmentation and representation from registered range and color images. Img. and Vis. Comp., 22, 703-717.
  • Bleser, G., Pastarmov, Y. and Stricker, D. (2005). Real-time 3D camera tracking for industrial augmented reality applications. Journal of Winter Sch. of Compt. Graphics, 47–54.
  • Bockholt, U., Bisler, A. and Becker, M., Müller-Wittig, W.K. and Voss, G. (2003). Augmented reality for enhancement of endoscopic interventions. Proc. IEEE Virtual Reality Conf., (pp. 97-101). Los Angeles, USA.
  • Bosche,F. (2010). Automated recognition of 3D CAD model objects in laser scans and calculation. Adv. Eng. Informatics, 24, 107-118.
  • Boufama, B. and Habed, A. (2004). Three-dimensional structure calculation: achieving accuracy without calibration. Img. and Vis. Comp., 22, 1039-1049.
  • Byne, J. H. M and Anderson, J. A. D. W. (1998). A CAD-based computer vision system. Img. and Vis. Comp., 16, 533-539.
  • Dornaika, F. and Chung, R. (2001). An algebraic approach to camera self-calibration Comp. Vis. and Img. Under., 83, 195-215.
  • Frere, D., Vandekerckhove, J., Moons, T. and Van Gool, L. (1998). Automatic modeling and 3D reconstruction of urban buildings from aerial imagery. IEEE Int. Geoscience and Rem. Sensing Symp. Proc., (pp. 2593-2596). Seattle.
  • Frueh, C. and Zakhor, A. (2001). 3D model generation for cities using aerial photograps and ground level laser scans. IEEE Conf. on Compt. Vis. and Pat. Recog., (2:2, pp. 31-38). Kauai, USA.
  • Gaspar, J., Grossmann, E. and Santos-Victor, J. (2001). Interactive reconstruction from an omnidirectional image. 9th Int. Symp. on Intel. Robotic Systems (SIRS’01), (pp. 139-147). Toulouse, France.
  • Grossmann, E., Ortin, D. and Santos-Victor, J. (2001), Algebraic aspects of reconstruction of structured scenes from one or more views, in: British Mach. Vis. Conf., (pp. 633-642). Manchester, UK.
  • Hua, L. and Weiyu, W. (2004). A new approach to image-based realistic architecture modeling with featured solid library. Auto. in Const. 13, 555-564.
  • Huertas, A., Nevita, R. and Landgrebe, D. (1999). Use of hyperspectral data with intensity images for automatic building modeling. Proc. of the Sec. Int. Conf. on Inf. Fusion, (pp. 680-687). Sunnyvale.
  • Kimber, M. and Blotter, J. (2006). A novel technique to determine difference contours between digital and physical objects for projection moiré interferometry. Opt. and Laser in Eng. 44, 25-40.
  • Lee, K., Wong, K. and Fung, S. Y. (2001). 3D face modeling from perspective-views and contour based generic model. Real- Time I., 7, 173-182.
  • Lindeberg, T. (1990). Scale-space for discrete signals. IEEE Trans. Pattern Recog. Mach. Intel., 12, 234–254.
  • Mülayim, A. Y., Yılmaz, U. and Atalay, V. (2003). Silhouette-based 3D model reconstruction from multiple images. IEEE Trans. on Systems, Man and Cybernetics, 33(4), 582-591.
  • Pratt,W.K. (1991). Digital image processing, second ed., (pp. 3-167). A Willey-Interscience Publication, New York.
  • Reed, M. K. and Allen, P. K. (1999). 3-D modeling from range imagery: An incremental method with a planning component. Img. and Vis. Comp., 17, 99-111.
  • Saha, P.K. (2005). Tensor scale: a local morphometric parameter with applications to computer vision and image processing. Compt. Vis. and Img. Under., 99, 384–413.
  • Song, L. and Wang, D., (2006). A novel grating matching method for 3D reconstruction. NDT & E Int., 39: 282-288.
  • Sturm, P., Cheng, Z. L. and Chen, P.C.Y. and Poo, A.N. (2005). Focal length calibration from two views: method and analysis of singular cases. Comp. Vis. and Image Under., 99, 58-95.
  • Song, L., Qu, X., Xu, K., Lv, L. (2005). Novel SFS-NDT in the field of detect detection, NDT&E Int. 38 (5), 381- 386.
  • Song L., Qu, X., Yang, Y., Yong, C. and Ye, S. (2005). Application of structured lighting sensor for online measurement. Opt. and Laser in Eng., 43 (10), 1118-1126.
  • Stamos, I. and Allen, P.E. (2000). 3-D Model construction using range and image data. Proceedings IEEE Conf. on Compt. Vis. and Pat. Recog., (pp. 531-536). Hilton Head Island.
  • Thrun, S. and Burgard, Fox, W. D. (2000). A Real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping. Proc. of Int. Conf. on Robotics and Automation, (1:4, pp. 321-328). San Francisco.
  • Tubic, D., Hébert, P. and Laurendeau, D. (2004). 3D surface modeling from curves. Img. and Vis. Comp., 22, 719-734.
  • Wesarg, S., Firle, E., Schwald, B., Seibert, H., Zogal, P. and Roeddiger, S. (2004). Accuracy of needle implantation in Brachtherapy using a medical AR system-a phantom study. SPIE Medical Imaging Symp., (pp. 341-352). San Diego, USA.
  • Witkin, A.P. (1983). Scale-space filtering. Proc. of 8th Int. Joint Conf. Art. Intel., (pp. 1019–1022). Karlsruhe, West Germany.
  • Xie, Z., Wang, J. and Zhang, Q. (2005). Complete 3D measurement in reverse engineering using a multi- probe system. Int. Journal of Mach. Tools Manuf., 45, 1474-1486.
  • Yang, W-B., Chen, M-B. and Yen, Y-N. (2011). An application of digital point cloud to historic architecture in digital archives. Advance in Eng. Soft. 42, 690-699.
  • Zhao, D., Li, S. (2005). A 3D image processing method for manufacturing process automation. Comps. in Industry, 56, 875-985.
  • Zhou, G. (1997). Primitive recognition using aspect-interpretation model matching in both CAD and LP based measurement systems. ISPRS J. of Photog. and Rem. Sensing, 52, 74-84.

Obtaining Three Dimensional Point Clouds from the Digital Images of Rectangular Prism Shaped Objects

Yıl 2012, Cilt: 2 Sayı: 2, 160 - 170, 31.12.2012

Öz

The processes applied on the pixels by the image processing methods provide us information about images. Image processing is a computer programming area which can be used in computer integrated industrial applications and it is one of the research areas of reverse engineering. In this study, a new system in which color digital images are interpreted by using image processing method was developed. The purpose of this study is to improve a system to interpret the images, which are taken with a hand camcorder or digital camera, and to obtain point clouds by evaluating with image processing and to convert these point clouds surface or solid model in a computer aided design program. In accordance with these purposes, the three dimensional point clouds are obtained from a rectangular prism shaped object in the specified area. These point clouds can easily be converted into three dimensional solid or surface models in a Computer Aided Design (CAD) program. In this reverse engineering study, the developed system is explained and sample parts are given

Kaynakça

  • As the number of points in point clouds which are obtained for the object is too much,
  • approximately 1-4 million, in the marked image to obtain its solid model needs some time,
  • In image processing which is done pixel to pixel according to the color analysis, color loss in the
  • image cause regional point loss, which causes some problems to model the part,
  • If the size of the object in the image and processed image is big, the size of the obtained point
  • cloud file becomes big.
  • It is aimed to obtain three dimensional point clouds for circular, curved and complex forms of objects in further studies.
  • Azuma, R., (1995). A survey of augmented reality. Computer Graphics SIGGRAPH Proc., 1-38.
  • Barbero B.R. and Ureta, E.S. (2011). Comparative study of different digitization techniques and their accuracy. Comp. Aided Design, 43, 188-206.
  • Benlamri, R. and Al-Marzooqi, Y. (2004). Free-from object segmentation and representation from registered range and color images. Img. and Vis. Comp., 22, 703-717.
  • Bleser, G., Pastarmov, Y. and Stricker, D. (2005). Real-time 3D camera tracking for industrial augmented reality applications. Journal of Winter Sch. of Compt. Graphics, 47–54.
  • Bockholt, U., Bisler, A. and Becker, M., Müller-Wittig, W.K. and Voss, G. (2003). Augmented reality for enhancement of endoscopic interventions. Proc. IEEE Virtual Reality Conf., (pp. 97-101). Los Angeles, USA.
  • Bosche,F. (2010). Automated recognition of 3D CAD model objects in laser scans and calculation. Adv. Eng. Informatics, 24, 107-118.
  • Boufama, B. and Habed, A. (2004). Three-dimensional structure calculation: achieving accuracy without calibration. Img. and Vis. Comp., 22, 1039-1049.
  • Byne, J. H. M and Anderson, J. A. D. W. (1998). A CAD-based computer vision system. Img. and Vis. Comp., 16, 533-539.
  • Dornaika, F. and Chung, R. (2001). An algebraic approach to camera self-calibration Comp. Vis. and Img. Under., 83, 195-215.
  • Frere, D., Vandekerckhove, J., Moons, T. and Van Gool, L. (1998). Automatic modeling and 3D reconstruction of urban buildings from aerial imagery. IEEE Int. Geoscience and Rem. Sensing Symp. Proc., (pp. 2593-2596). Seattle.
  • Frueh, C. and Zakhor, A. (2001). 3D model generation for cities using aerial photograps and ground level laser scans. IEEE Conf. on Compt. Vis. and Pat. Recog., (2:2, pp. 31-38). Kauai, USA.
  • Gaspar, J., Grossmann, E. and Santos-Victor, J. (2001). Interactive reconstruction from an omnidirectional image. 9th Int. Symp. on Intel. Robotic Systems (SIRS’01), (pp. 139-147). Toulouse, France.
  • Grossmann, E., Ortin, D. and Santos-Victor, J. (2001), Algebraic aspects of reconstruction of structured scenes from one or more views, in: British Mach. Vis. Conf., (pp. 633-642). Manchester, UK.
  • Hua, L. and Weiyu, W. (2004). A new approach to image-based realistic architecture modeling with featured solid library. Auto. in Const. 13, 555-564.
  • Huertas, A., Nevita, R. and Landgrebe, D. (1999). Use of hyperspectral data with intensity images for automatic building modeling. Proc. of the Sec. Int. Conf. on Inf. Fusion, (pp. 680-687). Sunnyvale.
  • Kimber, M. and Blotter, J. (2006). A novel technique to determine difference contours between digital and physical objects for projection moiré interferometry. Opt. and Laser in Eng. 44, 25-40.
  • Lee, K., Wong, K. and Fung, S. Y. (2001). 3D face modeling from perspective-views and contour based generic model. Real- Time I., 7, 173-182.
  • Lindeberg, T. (1990). Scale-space for discrete signals. IEEE Trans. Pattern Recog. Mach. Intel., 12, 234–254.
  • Mülayim, A. Y., Yılmaz, U. and Atalay, V. (2003). Silhouette-based 3D model reconstruction from multiple images. IEEE Trans. on Systems, Man and Cybernetics, 33(4), 582-591.
  • Pratt,W.K. (1991). Digital image processing, second ed., (pp. 3-167). A Willey-Interscience Publication, New York.
  • Reed, M. K. and Allen, P. K. (1999). 3-D modeling from range imagery: An incremental method with a planning component. Img. and Vis. Comp., 17, 99-111.
  • Saha, P.K. (2005). Tensor scale: a local morphometric parameter with applications to computer vision and image processing. Compt. Vis. and Img. Under., 99, 384–413.
  • Song, L. and Wang, D., (2006). A novel grating matching method for 3D reconstruction. NDT & E Int., 39: 282-288.
  • Sturm, P., Cheng, Z. L. and Chen, P.C.Y. and Poo, A.N. (2005). Focal length calibration from two views: method and analysis of singular cases. Comp. Vis. and Image Under., 99, 58-95.
  • Song, L., Qu, X., Xu, K., Lv, L. (2005). Novel SFS-NDT in the field of detect detection, NDT&E Int. 38 (5), 381- 386.
  • Song L., Qu, X., Yang, Y., Yong, C. and Ye, S. (2005). Application of structured lighting sensor for online measurement. Opt. and Laser in Eng., 43 (10), 1118-1126.
  • Stamos, I. and Allen, P.E. (2000). 3-D Model construction using range and image data. Proceedings IEEE Conf. on Compt. Vis. and Pat. Recog., (pp. 531-536). Hilton Head Island.
  • Thrun, S. and Burgard, Fox, W. D. (2000). A Real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping. Proc. of Int. Conf. on Robotics and Automation, (1:4, pp. 321-328). San Francisco.
  • Tubic, D., Hébert, P. and Laurendeau, D. (2004). 3D surface modeling from curves. Img. and Vis. Comp., 22, 719-734.
  • Wesarg, S., Firle, E., Schwald, B., Seibert, H., Zogal, P. and Roeddiger, S. (2004). Accuracy of needle implantation in Brachtherapy using a medical AR system-a phantom study. SPIE Medical Imaging Symp., (pp. 341-352). San Diego, USA.
  • Witkin, A.P. (1983). Scale-space filtering. Proc. of 8th Int. Joint Conf. Art. Intel., (pp. 1019–1022). Karlsruhe, West Germany.
  • Xie, Z., Wang, J. and Zhang, Q. (2005). Complete 3D measurement in reverse engineering using a multi- probe system. Int. Journal of Mach. Tools Manuf., 45, 1474-1486.
  • Yang, W-B., Chen, M-B. and Yen, Y-N. (2011). An application of digital point cloud to historic architecture in digital archives. Advance in Eng. Soft. 42, 690-699.
  • Zhao, D., Li, S. (2005). A 3D image processing method for manufacturing process automation. Comps. in Industry, 56, 875-985.
  • Zhou, G. (1997). Primitive recognition using aspect-interpretation model matching in both CAD and LP based measurement systems. ISPRS J. of Photog. and Rem. Sensing, 52, 74-84.
Toplam 43 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Gürcan Samtaş Bu kişi benim

Mahmut Gülesin Bu kişi benim

Yayımlanma Tarihi 31 Aralık 2012
Gönderilme Tarihi 5 Ocak 2015
Yayımlandığı Sayı Yıl 2012 Cilt: 2 Sayı: 2

Kaynak Göster

APA Samtaş, G., & Gülesin, M. (2012). Obtaining Three Dimensional Point Clouds from the Digital Images of Rectangular Prism Shaped Objects. Ejovoc (Electronic Journal of Vocational Colleges), 2(2), 160-170.