Haar-like features have been successfully used for image classification and object detection . It has been used for real-time face detection algorithm proposed in .

Parameters

int_image : (M, N) ndarray

Integral image for which the features need to be computed.

r : int

Row-coordinate of top left corner of the detection window.

c : int

Column-coordinate of top left corner of the detection window.

width : int

Width of the detection window.

height : int

Height of the detection window.

feature_type : str

The type of feature to consider:

• 'type-2-x': 2 rectangles varying along the x axis;

• 'type-2-y': 2 rectangles varying along the y axis;

• 'type-3-x': 3 rectangles varying along the x axis;

• 'type-3-y': 3 rectangles varying along the y axis;

• 'type-4': 4 rectangles varying along x and y axis.

Returns

haar_features : (n_features,) ndarray

Resulting Haar-like features. Each value is equal to the subtraction of sums of the positive and negative rectangles. The data type depends of the data type of :None:None:`int_image`: :None:None:`int` when the data type of :None:None:`int_image` is uint or :None:None:`int` and :None:None:`float` when the data type of :None:None:`int_image` is :None:None:`float`.

Compute the Haar-like features for a region of interest (ROI) of an integral image.

Examples

See :

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