ArrayFire: sift (original) (raw)
SIFT feature detector and descriptor extractor. More...
| Functions | |
|---|---|
| AFAPI void | sift (features &feat, array &desc, const array &in, const unsigned n_layers=3, const float contrast_thr=0.04f, const float edge_thr=10.f, const float init_sigma=1.6f, const bool double_input=true, const float intensity_scale=0.00390625f, const float feature_ratio=0.05f) |
| C++ Interface for SIFT feature detector and descriptor. More... | |
| AFAPI void | gloh (features &feat, array &desc, const array &in, const unsigned n_layers=3, const float contrast_thr=0.04f, const float edge_thr=10.f, const float init_sigma=1.6f, const bool double_input=true, const float intensity_scale=0.00390625f, const float feature_ratio=0.05f) |
| C++ Interface for SIFT feature detector and GLOH descriptor. More... | |
| AFAPI af_err | af_sift (af_features *feat, af_array *desc, const af_array in, const unsigned n_layers, const float contrast_thr, const float edge_thr, const float init_sigma, const bool double_input, const float intensity_scale, const float feature_ratio) |
| C++ Interface for SIFT feature detector and descriptor. More... | |
| AFAPI af_err | af_gloh (af_features *feat, af_array *desc, const af_array in, const unsigned n_layers, const float contrast_thr, const float edge_thr, const float init_sigma, const bool double_input, const float intensity_scale, const float feature_ratio) |
| C++ Interface for SIFT feature detector and GLOH descriptor. More... | |
SIFT feature detector and descriptor extractor.
Detects features and extract descriptors using the Scale Invariant Feature Transform (SIFT), by David Lowe.
Lowe, D. G., "Distinctive Image Features from Scale-Invariant Keypoints", International Journal of Computer Vision, 60, 2, pp. 91-110, 2004.
◆ af_gloh()
| AFAPI af_err af_gloh | ( | af_features * | feat, |
|---|---|---|---|
| af_array * | desc, | ||
| const af_array | in, | ||
| const unsigned | n_layers, | ||
| const float | contrast_thr, | ||
| const float | edge_thr, | ||
| const float | init_sigma, | ||
| const bool | double_input, | ||
| const float | intensity_scale, | ||
| const float | feature_ratio | ||
| ) |
C++ Interface for SIFT feature detector and GLOH descriptor.
Parameters
| [out] | feat | af_features object composed of arrays for x and y coordinates, score, orientation and size of selected features |
|---|---|---|
| [out] | desc | Nx272 array containing extracted GLOH descriptors, where N is the number of features found by SIFT |
| [in] | in | array containing a grayscale image (color images are not supported) |
| [in] | n_layers | number of layers per octave, the number of octaves is computed automatically according to the input image dimensions, the original SIFT paper suggests 3 |
| [in] | contrast_thr | threshold used to filter out features that have low contrast, the original SIFT paper suggests 0.04 |
| [in] | edge_thr | threshold used to filter out features that are too edge-like, the original SIFT paper suggests 10.0 |
| [in] | init_sigma | the sigma value used to filter the input image at the first octave, the original SIFT paper suggests 1.6 |
| [in] | double_input | if true, the input image dimensions will be doubled and the doubled image will be used for the first octave |
| [in] | intensity_scale | the inverse of the difference between the minimum and maximum grayscale intensity value, e.g.: if the ranges are 0-256, the proper intensity_scale value is 1/256, if the ranges are 0-1, the proper intensity-scale value is 1/1 |
| [in] | feature_ratio | maximum ratio of features to detect, the maximum number of features is calculated by feature_ratio * in.elements(). The maximum number of features is not based on the score, instead, features detected after the limit is reached are discarded |
◆ af_sift()
| AFAPI af_err af_sift | ( | af_features * | feat, |
|---|---|---|---|
| af_array * | desc, | ||
| const af_array | in, | ||
| const unsigned | n_layers, | ||
| const float | contrast_thr, | ||
| const float | edge_thr, | ||
| const float | init_sigma, | ||
| const bool | double_input, | ||
| const float | intensity_scale, | ||
| const float | feature_ratio | ||
| ) |
C++ Interface for SIFT feature detector and descriptor.
Parameters
| [out] | feat | af_features object composed of arrays for x and y coordinates, score, orientation and size of selected features |
|---|---|---|
| [out] | desc | Nx128 array containing extracted descriptors, where N is the number of features found by SIFT |
| [in] | in | array containing a grayscale image (color images are not supported) |
| [in] | n_layers | number of layers per octave, the number of octaves is computed automatically according to the input image dimensions, the original SIFT paper suggests 3 |
| [in] | contrast_thr | threshold used to filter out features that have low contrast, the original SIFT paper suggests 0.04 |
| [in] | edge_thr | threshold used to filter out features that are too edge-like, the original SIFT paper suggests 10.0 |
| [in] | init_sigma | the sigma value used to filter the input image at the first octave, the original SIFT paper suggests 1.6 |
| [in] | double_input | if true, the input image dimensions will be doubled and the doubled image will be used for the first octave |
| [in] | intensity_scale | the inverse of the difference between the minimum and maximum grayscale intensity value, e.g.: if the ranges are 0-256, the proper intensity_scale value is 1/256, if the ranges are 0-1, the proper intensity-scale value is 1/1 |
| [in] | feature_ratio | maximum ratio of features to detect, the maximum number of features is calculated by feature_ratio * in.elements(). The maximum number of features is not based on the score, instead, features detected after the limit is reached are discarded |
◆ gloh()
| AFAPI void gloh | ( | features & | feat, |
|---|---|---|---|
| array & | desc, | ||
| const array & | in, | ||
| const unsigned | n_layers = 3, | ||
| const float | contrast_thr = 0.04f, | ||
| const float | edge_thr = 10.f, | ||
| const float | init_sigma = 1.6f, | ||
| const bool | double_input = true, | ||
| const float | intensity_scale = 0.00390625f, | ||
| const float | feature_ratio = 0.05f | ||
| ) |
C++ Interface for SIFT feature detector and GLOH descriptor.
Parameters
| [out] | feat | features object composed of arrays for x and y coordinates, score, orientation and size of selected features |
|---|---|---|
| [out] | desc | Nx272 array containing extracted GLOH descriptors, where N is the number of features found by SIFT |
| [in] | in | array containing a grayscale image (color images are not supported) |
| [in] | n_layers | number of layers per octave, the number of octaves is computed automatically according to the input image dimensions, the original SIFT paper suggests 3 |
| [in] | contrast_thr | threshold used to filter out features that have low contrast, the original SIFT paper suggests 0.04 |
| [in] | edge_thr | threshold used to filter out features that are too edge-like, the original SIFT paper suggests 10.0 |
| [in] | init_sigma | the sigma value used to filter the input image at the first octave, the original SIFT paper suggests 1.6 |
| [in] | double_input | if true, the input image dimensions will be doubled and the doubled image will be used for the first octave |
| [in] | intensity_scale | the inverse of the difference between the minimum and maximum grayscale intensity value, e.g.: if the ranges are 0-256, the proper intensity_scale value is 1/256, if the ranges are 0-1, the proper intensity-scale value is 1/1 |
| [in] | feature_ratio | maximum ratio of features to detect, the maximum number of features is calculated by feature_ratio * in.elements(). The maximum number of features is not based on the score, instead, features detected after the limit is reached are discarded |
| AFAPI void sift | ( | features & | feat, |
|---|---|---|---|
| array & | desc, | ||
| const array & | in, | ||
| const unsigned | n_layers = 3, | ||
| const float | contrast_thr = 0.04f, | ||
| const float | edge_thr = 10.f, | ||
| const float | init_sigma = 1.6f, | ||
| const bool | double_input = true, | ||
| const float | intensity_scale = 0.00390625f, | ||
| const float | feature_ratio = 0.05f | ||
| ) |
C++ Interface for SIFT feature detector and descriptor.
Parameters
| [out] | feat | features object composed of arrays for x and y coordinates, score, orientation and size of selected features |
|---|---|---|
| [out] | desc | Nx128 array containing extracted descriptors, where N is the number of features found by SIFT |
| [in] | in | array containing a grayscale image (color images are not supported) |
| [in] | n_layers | number of layers per octave, the number of octaves is computed automatically according to the input image dimensions, the original SIFT paper suggests 3 |
| [in] | contrast_thr | threshold used to filter out features that have low contrast, the original SIFT paper suggests 0.04 |
| [in] | edge_thr | threshold used to filter out features that are too edge-like, the original SIFT paper suggests 10.0 |
| [in] | init_sigma | the sigma value used to filter the input image at the first octave, the original SIFT paper suggests 1.6 |
| [in] | double_input | if true, the input image dimensions will be doubled and the doubled image will be used for the first octave |
| [in] | intensity_scale | the inverse of the difference between the minimum and maximum grayscale intensity value, e.g.: if the ranges are 0-256, the proper intensity_scale value is 1/256, if the ranges are 0-1, the proper intensity-scale value is 1/1 |
| [in] | feature_ratio | maximum ratio of features to detect, the maximum number of features is calculated by feature_ratio * in.elements(). The maximum number of features is not based on the score, instead, features detected after the limit is reached are discarded |