Advertisement

Design and Implementation ACO Based Edge Detection on the Fusion of Hue and PCA

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 410)

Abstract

The edge detection has become very popular due to its use in various vision applications. Edge detections produces a black and white image where objects are distinguished by lines (either objects boundary comes in black color or white color) depends upon where sharp changes exist. Many techniques have been proposed so far for improving the accuracy of the edge detection techniques. The Fusion of PCA and HUE based edge detector has shown quite better results over the available techniques. But still fusion technique forms unwanted edges so this paper has proposed a new Color and ACO based edge detection technique. The MATLAB tool is used to design and implement the proposed edge detection. Various kinds of images has been considered to evaluate the effectiveness of the proposed technique. Pratt figure of merit and F-measure parameters has been used to evaluate the effectiveness of the available edge detectors.

References

  1. 1.
    Ju, Z.W., Chen, J.Z., Zhou, J.L.: Image segmentation based on edge detection using K-means and an improved ant colony optimization. In: Proceedings of the International Conference on Machine Learning and Cybernetics, Tianjin, 14–17 July, IEEE (2013)Google Scholar
  2. 2.
    Lei, Tao, Fan, Yangyu, Wang, Yi: Colour edge detection based on the fusion of hue component and principal component analysis. IET Image Proc. 8(1), 44–55 (2014)CrossRefGoogle Scholar
  3. 3.
    Deng, C.X., Wang, G.B., Yang, X.R.: Image edge detection algorithm based on improved canny operator. In: Proceedings of the 2013 International Conference on Wavelet Analysis and Pattern Recognition IEEE, Tianjin, 14–17 July (2013)Google Scholar
  4. 4.
    Manish, T.I., Murugan, D., Ganesh Kumar, T.: Hybrid edge detection using canny and ant colony optimization. Commun. Inf. Sci. Manag. Eng. 3(8), 402–405 (2013)Google Scholar
  5. 5.
    Gupta1, C., Gupta, S.: Edge detection of an image based on ant colony optimization technique. Int. J. Sci. Res. (IJSR) 2(6) (2013)Google Scholar
  6. 6.
    Thukaram, P., Saritha, S.J.: Image edge detection using improved ant colony optimization algorithm. Int. J. Res. Comput. Commun. Technol. 2(11), 1256–1260 (2013)Google Scholar
  7. 7.
    Jin, L., Song, E., Li, L., Li, X.: A quaternion gradiet operator for color image edge detection. ICIP IEEE (2013)Google Scholar
  8. 8.
    Dikbas, S., Arici, T., Altunbasak, Y.: Chrominance edge preserving grayscale transformation with approximate first principal component for color edge detection. Proc. IEEE Conf. Image Process. (ICIP’07), 497–500 (2007)Google Scholar
  9. 9.
    Mahajanl, S., Singh, A.: Integrated PCA & DCT based fusion using consistency verification & non-linear enhancement. IJECS 3(3), 4030–4039 (2014)Google Scholar
  10. 10.
    Tung, C.H., Han, G.W.: Efficient image edge detection using ant colony optimizationGoogle Scholar
  11. 11.
    Rahebi, J., Tajik, H.R.: Biomedical image edge detection using an ant colony optimization based on artificial neural networks. Int. J. Eng. Sci. Technol. (IJEST) 3(12), 8211–8218 (2011) (ISSN:0975-5462)Google Scholar
  12. 12.
    Tyagi, Y., Puntambekar, T.A., Sexena, P., Tanwani, S.: A hybrid approach to edge detection using ant colony optimization and fuzzy logic. Int. J. Hybrid Inf. Technol. 5(1) (2012)Google Scholar
  13. 13.
    Lei, T., Fan, Y., Wang, Y.: Colour edge detection based on the fusion of hue component and principal component analysis. IET Image Proc. 8(1), 44–55 (2014)CrossRefGoogle Scholar
  14. 14.
    Walia, S.S., Singh, G.: Improved color edge detector using fuzzy set theory. Int. J. Adv. Res. Comput. Sci. Electronics Eng. (IJARCSEE) 3(5) (2014)Google Scholar
  15. 15.
    Powers, D.M.W.: Evaluation: from precision, recall and F-factor to ROC, informedness, markedness and correlation (2007)Google Scholar
  16. 16.
    Mahajan, S., Singh, A.: Evaluated the performance of integrated PCA & DCT based fusion using consistency verification & non-linear enhancement. IJESRT, (2014) Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.DAVIETJalandharIndia

Personalised recommendations