# es¶

menpo.feature.es(pixels, verbose=False)[source]

Extracts Edge Structure (ES) features from the input image. The output image has N * C number of channels, where N is the number of channels of the original image and C = 2.

Parameters
• pixels (Image or subclass or (C, X, Y, ..., Z) ndarray) – Either an image object itself or an array where the first axis represents the number of channels. This means an N-dimensional image is represented by an N+1 dimensional array.

• verbose (bool, optional) – Flag to print ES related information.

Returns

es (Image or subclass or (X, Y, ..., Z, C) ndarray) – The ES features image. It has the same type and shape as the input pixels. The output number of channels is C = 2.

Raises

ValueError – Image has to be 2D in order to extract ES features.

References

1

T. Cootes, C. Taylor, “On representing edge structure for model matching”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2001.