Efficient Color Boundary Detection with Color-Opponent Mechanisms

Yang, Kai-Fu; Gao, Shaobing; Li, Chaoyi; Li, Yongjie

doi:10.1109/cvpr.2013.362

Cited by 65 publications

(63 citation statements)

References 35 publications

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“…Because of the imbalance, these DO cells would respond best to (and enhance greatly) the edges defined by the chromatic and luminance differences [7,13]. As most edges in the real world do combine luminance and chromatic differences [29], such cells would be extremely useful for the analysis of natural scenes. Furthermore, the unbalanced center-surround RF structure endows the DO cells with a band-pass and partially low-pass spatial frequency tuning property [23], which ensures that the DO cells can also transfer partially the smoothed low-frequency global (possibly the light source) color information while smoothing and suppressing the color of local surfaces.…”

Section: Discussionmentioning

confidence: 99%

A Color Constancy Model with Double-Opponency Mechanisms

Gao

Yang

et al. 2013

2013 IEEE International Conference on Computer Vision

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Section: Discussionmentioning

confidence: 99%

A Color Constancy Model with Double-Opponency Mechanisms

Gao

Yang

et al. 2013

2013 IEEE International Conference on Computer Vision

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“…Figure 2 shows that they have a negative response to the green if cells have a positive response to the red [66]. Figure 3 illustrates that on the basic of characteristic that visual cells have different responses to different hue [22],we can quickly determine the boundaries of objects with specific hue [66].…”

Section: Boundary Detectionmentioning

confidence: 96%

Skin color modeling for face detection and segmentation: a review and a new approach

Chen

Wang

Jiang

et al. 2014

Multimed Tools Appl

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Detecting skin-colored pixels, although seems a straightforward easy task, has proven to be quite a challenging task in images that are captured under complex unconstrained imaging conditions. Color segmentation is an important method of segmenting the body in images. In this paper, we first provides a review of skin color modeling research works for face detection. In particular, we focus on discussing the challenges of skin color modeling, detection, and segmentation, and then we present the skin color modeling and region-based skin segmentation. We also propose a new approach to analyze the hue characteristics of monitoring personnel in coal mine. We determine the skin color boundaries of the miners using the boundary detection method based on the response of visual hue. And then, we apply to determining hue area method using dual hue detector to segment skin color for miners. Experiments show that the method has excellent ability to segment skin regions of miners. We also summarize the most widely used methods for skin detection approaches and collecting their numerical evaluation results.

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“…On the contrary, vector-valued techniques regard the color information as vectors [30][31][32][33][34][35][36]. Furthermore, biologically-inspired edge-detection techniques exist (e.g., [37]), which are based on the concept of color-opponency and use color differences as the basis for edge detection. None of these methods distinguish between edges in the sky and edges in the ground region of an image and are therefore not relevant for our problem formulation; for further reading, we refer to available reviews [38][39][40][41].…”

Section: Related Work: Edge Suppressionmentioning

confidence: 99%

Cloud-Edge Suppression for Visual Outdoor Navigation

Hoffmann

Möller

2017

Robotics

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Outdoor environments pose multiple challenges for the visual navigation of robots, like changing illumination conditions, seasonal changes, dynamic environments and non-planar terrain. Illumination changes are mostly caused by the movement of the Sun and by changing cloud cover. Moving clouds themselves also are a dynamic aspect of a visual scene. For visual homing algorithms, which compute the direction to a previously visited place by comparing the current view with a snapshot taken at that place, in particular, the changing cloud cover poses a problem, since cloud movements do not correspond to movements of the camera and thus constitute misleading information. We propose an edge-filtering method operating on linearly-transformed RGB channels, which reliably detects edges in the ground region of the image while suppressing edges in the sky region. To fulfill this criterion, the factors for the linear transformation of the RGB channels are optimized systematically concerning this special requirement. Furthermore, we test the proposed linear transformation on an existing visual homing algorithm (MinWarping) and show that the performance of the visual homing method is significantly improved compared to the use of edge-filtering methods on alternative color information.

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Efficient Color Boundary Detection with Color-Opponent Mechanisms

Cited by 65 publications

References 35 publications

A Color Constancy Model with Double-Opponency Mechanisms

A Color Constancy Model with Double-Opponency Mechanisms

Skin color modeling for face detection and segmentation: a review and a new approach

Cloud-Edge Suppression for Visual Outdoor Navigation

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