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Research Article | Open | Published:

Texture-Gradient-Based Contour Detection

Abstract

In this paper, a new biologically motivated method is proposed to effectively detect perceptually homogenous region boundaries. This method integrates the measure of spatial variations in texture with the intensity gradients. In the first stage, texture representation is calculated using the nondecimated complex wavelet transform. In the second stage, gradient images are computed for each of the texture features, as well as for grey scale intensity. These gradients are efficiently estimated using a new proposed algorithm based on a hypothesis model of the human visual system. After that, combining these gradient images, a region gradient which highlights the region boundaries is obtained. Nonmaximum suppression and then thresholding with hysteresis is used to detect contour map from the region gradients. Natural and textured images with associated ground truth contour maps are used to evaluate the operation of the proposed method. Experimental results demonstrate that the proposed contour detection method presents more effective performance than conventional approaches.

References

  1. 1.

    Canny J: Computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 1986, 8(6):679–698.

  2. 2.

    Shen J, Castan S: An optimal linear operator for step edge detection. Graphical Models and Image Processing 1992, 54(1):112–133.

  3. 3.

    Rakesh RR, Chaudhuri P, Murthy CA: Thresholding in edge detection: a statistical approach. IEEE Transactions on Image Processing 2004, 13(7):927–936. 10.1109/TIP.2004.828404

  4. 4.

    Zhaoping L: Pre-attentive segmentation in the primary visual cortex. Spatial Vision 2000, 13(1):25–50. 10.1163/156856800741009

  5. 5.

    Lee TS: Computations in the early visual cortex. Journal of Physiology 2003, 97(2–3):121–139.

  6. 6.

    Jones HE, Grieve KL, Wang W, Sillito AM: Surround suppression in primate V1. Journal of Neurophysiology 2001, 86(4):2011–2028.

  7. 7.

    Nothdurf H-C, Gallant JL, Van Essen DC: Response modulation by texture surround in primate area V1: correlates of 'popout' under anesthesia. Visual Neuroscience 1999, 16(1):15–34.

  8. 8.

    Petkov N, Westenberg MA: Suppression of contour perception by band-limited noise and its relation to nonclassical receptive field inhibition. Biological Cybernetics 2003, 88(3):236–246. 10.1007/s00422-002-0378-2

  9. 9.

    Grigorescu C, Petkov N, Westenberg MA: Contour detection based on nonclassical receptive field inhibition. IEEE Transactions on Image Processing 2003, 12(7):729–739. 10.1109/TIP.2003.814250

  10. 10.

    Malik J, Perona P: Preattentive texture discrimination with early vision mechanisms. Journal of the Optical Society of America A 1990, 7(5):923–932. 10.1364/JOSAA.7.000923

  11. 11.

    Grigorescu SE, Petkov N, Kruizinga P: Comparison of texture features based on Gabor filters. IEEE Transactions on Image Processing 2002, 11(10):1160–1167. 10.1109/TIP.2002.804262

  12. 12.

    Hill PR, Canagarajah CN, Bull DR: Image segmentation using a texture gradient based watershed transform. IEEE Transactions on Image Processing 2003, 12(12):1618–1633. 10.1109/TIP.2003.819311

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Author information

Correspondence to Nasser Chaji.

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Keywords

  • Texture Feature
  • Region Boundary
  • Homogenous Region
  • Human Visual System
  • Texture Image