Abstract
The objective of this work is to develop a highly robust 3D part localization and recognition algorithm. This research work is driven by the needs specified by enterprises with small production series that seek for full robotic automation in their production line, which processes a wide range of products and cannot use dedicated identification devices due to technological processes. With the correct classification of the part, the robot will be able to autonomously select the correct program to execute. For this purpose, the Perfect Match algorithm, which is known by its computational efficiency, high precision and robustness, was adapted for object recognition achieving a 99.7% of classification rate. The expected practical implication of this work is contributing to the integration of industrial robots in highly dynamic and specialized lines, reducing the companies’ dependency on skilled operators.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Sansoni, G., Trebeschi, M., Docchio, F.: State-of-the-art and applications of 3D imaging sensors in industry. Cultural Heritage, Medicine and Criminal Investigation Sensors (2009)
Ben-Tzvi, P., Charifa, S., Shick, M.: Extraction of 3D images using pitch-actuated 2D laser range finder for robotic vision, pp. 1–6 (October 2010)
Santolaria, J., Pastor, J.J., Brosed, F.J., Aguilar, J.J.: A one-step intrinsic and extrinsic calibration method for laser line scanner operation in coordinate measuring machines. IOP Publishing Ltd. (2009)
Hernández-López, J.-J., Quintanilla-Olvera, A.-L., López-Ramírez, J.-L., Rangel-Butanda, F.-J., Ibarra-Manzano, M.-A., Almanza-Ojeda, D.-L.: Detecting objects using color and depth segmentation with kinect sensor. In: The 2012 Iberoamerican Conference on Electronics Engineering and Computer Science (2012)
Yan CuiSchuon, S., Chan, D., Thrun, S., Theobalt, C.: 3D shape scanning with a time-of-flight camera. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR (2010)
Mingqiang, Y., Kidiyo, K., Joseph, R.: A survey of shape feature extraction techniques. Pattern Recognition (2008)
Paschalakis, Lee, S., Kent, P.: Pattern recognition in grey level images using moment based invariant features. In: Seventh International Conference on Image Processing And Its Applications (Conf. Publ. No. 465), vol. 1, pp. 245–249 (1999)
Flusser, J., Suk, T., Zitov, B.: Moments and moment invariants in pattern recognition. John Wiley and Sons Ltd., Chichester (2009)
Khabou, M.A., Hermi, L., Rhouma, M.B.H.: Shape recognition using eigenvalue of the dirichlet laplacian. Pattern Recognition 40 (2007)
Pan, H., Xia, L.-Z.: Efficient object recognition using boundary representation and wavelet neural network. IEEE Transactions on Neural Networks (2008)
Dale, M.P., Joshi, M.A.: Fingerprint matching using transform features. IEEE Region 10 Conference TENCON (2008)
Zavadil, Santos, V., Tuma., J.: Traffic lights recognition for robotic competition. Inproceedings of MATLAB (2011)
Ferreira, M., Moreira, A.P., Neto, P.: A low-cost laser scanning solution for flexible robotic cells: spray coating. The International Journal of Advanced Manufacturing Technology 58, 1031–1041 (2012)
Lauer, M., Lange, S., Riedmiller, M.: Calculating the perfect match: an efficient and accurate approach for robot self-localization. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds.) RoboCup 2005. LNCS (LNAI), vol. 4020, pp. 142–153. Springer, Heidelberg (2006)
Pinto, M., Moreira, A.P., Matos, A., Sobreira, H.: Novel 3D Matching self-localization algorithm. International Journal of Advances in Engineering & Technology (November 2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rocha, L.F., Ferreira, M., Veiga, G., Moreira, A.P., Santos, V. (2013). Recognizing Industrial Manipulated Parts Using the Perfect Match Algorithm. In: Neto, P., Moreira, A.P. (eds) Robotics in Smart Manufacturing. WRSM 2013. Communications in Computer and Information Science, vol 371. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39223-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-39223-8_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39222-1
Online ISBN: 978-3-642-39223-8
eBook Packages: Computer ScienceComputer Science (R0)