Abstract
As to aided driving by harvesting robot, there is the large amount of image data processing, meanwhile, harvesting robot requires real-time image processing and to calculate the linear parameters in a straight line detection of the walking target process. This paper presents a hardware processing platform to TMS320DM6437 digital signal processor as the core processing chip, and an improved Hough transform algorithm which is based on a determined point is proposed to complete line detection. A camera is to be fitted on the left top of the combine harvester in order to capture images of farmland scenes in the process of harvesting. At first, according to different color characteristics of harvested areas and non-harvested areas, improved methods of Maximum entropy threshold segmentation and morphological approach are employed to determine candidate points of walking goal line. Then the candidate points are selected as the point set. Finally, the improved Hough transform based on a determined point is applied to complete line detection. The algorithm simplifies binary map to unitary map. Comparing with the traditional Hough transform, it saves computing time, and reduces the parameter space greatly. After multiple images processing, tests show that this detection method can detect real-time parameters of harvesting robot’s walking goal line, and the algorithm is well proved with respect to its speed, anti-interference and accuracy.
Chapter PDF
Similar content being viewed by others
References
Zhou, J., Ji, C., Liu, C.: Visual navigation system of agricultural wheeled-mobile robot. Transactions of the Chinese Society for Agricultural Machinery 36(3), 90–94 (2005)
Shen, M., Ji, C.: Development and Prospect of Vision Guidance of Agricultural Robot. Transactions of the Chinese Society for Agricultural Machinery 32(1), 109–110 (2001)
Zhao, B., Wang, M., Mao, E., Zhang, X., Song, Z.: Recognition and classification for vision navigation application environment of agriculturalvehicle. Transactions of the Chinese Society for Agricultural Machinery 40(7), 166–170 (2009)
Ma, Z.-F., Zhao, B.-J., He, P.-K.: High-Speed Image Sampling And Dectection System Based on DSPC64X. Transactions of Beijing Institute of Technology 25(7), 628–631 (2005)
Cao, Q., Wang, K., Yang, Y., Shi, X.: Identifying the navigation route based on TMS320DM642 for agriculture visual robot. Transactions of the Chinese Society for Agricultural Machinery 40(7), 171–175 (2009)
Texas Instruments, TVP5146[S].8(SLES084C) (2007)
Texas Instruments, TMS320DM6437 Digital Media Processor[S], 6(SPRS345D) (2008)
Ni, C., Li, X., Wang, X.: Grain harvesting machinery Insider. Publishing house of electronics industry, Beijing (2008)
Navon, E., Miller, O., Averbuch, A.: Color image segmentation based on adaptive local thresholds. Image and Vision Computing 23(1), 69–85 (2005)
Otsu, N.: A Threshold Selection Method From Gray Level Histograms. IEEE Trans. on Syst. Man Cybernet SMC-9, 62–66 (1979)
Ridler, T.W., Calvard, S.: Picture thresholding using an iterative selection method. IEEE Transactions on Systems, Man and Cybernetics, 630–632 (1978)
Guo, H., Tian, T., Wang, L., Zhang, C.: Image Segmentation Using the Maximum Entropy of the Two-Dimensional Bound Histogram. Acta Optica Sinica 26(4), 506–509 (2006)
Zhang, F., Wang, K., Shi, X.: Vehicle flow detection system based on machine vision. Control & Automation 24, 138–140 (2008)
Cao, Q., Wang, K.: Vision Navigation Based on Agricultural Non-structural Characteristic. Transactions of the Chinese Society for Agricultural Machinery 40(1), 187–189 (2009)
Zhao, Y., Chen, B., Wang, S., Dai, F.: Fast detection of furrows based on machine vision on autonomous mobile robot. Transactions of the Chinese Society for Agricultural Machinery 37(4), 83–86 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 IFIP International Federation for Information Processing
About this paper
Cite this paper
Wu, G., Tan, Y., Zheng, Y., Wang, S. (2012). Walking Goal Line Detection Based on DM6437 on Harvesting Robot. In: Li, D., Chen, Y. (eds) Computer and Computing Technologies in Agriculture V. CCTA 2011. IFIP Advances in Information and Communication Technology, vol 370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27275-2_40
Download citation
DOI: https://doi.org/10.1007/978-3-642-27275-2_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27274-5
Online ISBN: 978-3-642-27275-2
eBook Packages: Computer ScienceComputer Science (R0)