Efficient Color Boundary Detection with Color-opponent Mechanisms

CVPR2013 Posters

Outline

Introduction Approach Experiments Conclusions

Introduction

Introduction

Propose a new framework for boundary detection in complex natural scenes based on the color-opponent mechanisms of the visual system.

Image source:http://en.wikipedia.org/wiki/Opponent_process

Introduction One of the key limitations of opponent-based

approaches is that they are

blind to the luminance-defined boundaries. In order to obtain the complete contours of

objects, these methods had to spend extra computational cost to combine more cues to detect luminance boundaries [3].

[3] D. R. Martin, C. C. Fowlkes, and J. Malik, "Learning to detect natural image boundaries using local brightness, color, and texture cues," IEEE Trans. on PAMI, vol. 26, pp. 530-549, 2004.

Introduction Simulate the biological mechanisms of

color information processing along the Retina-LGN-Cortex visual pathway

Image source:http://en.wikipedia.org/wiki/Opponent_process

Introduction

Image source:[20] S. G. Solomon and P. Lennie, "The machinery of colourvision," Nature Reviews Neuroscience, vol. 8, pp. 276-286, 2007.

Introduction

Color Mechanisms in the Visual System. Properties : 1. Trichromacy. 2. Two opponent channels. 3. Color opponency.

Approach

Boundary Detection System : 1.Cone Layer 2.Ganglion/LGN Layer 3.Cortex Layer

A feedforward hierarchical system

1.Cone Layer

Type II cells in the ganglion/LGN layer is mainly for the perception of color region.

Four channels: red (R), green (G), blue (B) and yellow (Y) components, where Y = (R+G)/2.

Gaussian filters are used to simulate the receptive field of the cones in the retina.

Outputs:

Approach

Boundary Detection System : 1.Cone Layer 2.Ganglion/LGN Layer 3.Cortex Layer

2.Ganglion/LGN Layer

Single-opponent cells in ganglion/LGN layer areimportant for separating color and achromatic information,which is clearly shown by Equation 1.

w1 > 0 and w2 < 0 response : R-on/G-off cellsw1 < 0 and w2 > 0 response : R-off/G-on cells

Approach

Boundary Detection System : 1.Cone Layer 2.Ganglion/LGN Layer 3.Cortex Layer

3.Cortex Layer

In the cortex layer of V1, the receptive fields of most color- and color-luminance-sensitive neurons are both chromatically and spatially opponent.

3.Cortex Layer

3.Cortex Layer

The boundary responses at each orientation is given by (6)

3.Cortex Layer

The boundaries are detected in four channels (i.e., R+ wG, wR+ G, B+ wY and wB+Y ) with Equations 1-8.

Experiments

Experiments

Experiments

Experiments

Experiments

Experiments

Experiments

Conclusions

1. Presented a novel biologically plausible computational model for contour detection of color images.

2. Our model exhibits excellent capability of detecting both color and luminance boundaries synchronously in a time-saving manner.