Classes
class	Image
	Wrapper of old C-style OpenCV IplImage with some processing functionalities. More...
class	ImageRoi
	2D roi More...
Functions
void	backProject (const cv::Mat &image, const cv::MatND &hist, int threshold, cv::Mat &result, int dilateIterations=0, int dilateSize=3, int erodeIterations=0, int erodeSize=3)
	backProject generate a binary image resulting of thresholding the per-pixel backprojection of a H-S histogram to a color image
void	calcHSVHist (const cv::Mat &src, cv::MatND &histogram)
	calcHSVHist compute and return a Hue-Saturation histogram of a given image
void	calcHSVHist (const std::vector< cv::Mat > &src, std::vector< cv::MatND > &histograms)
	calcHSVHist compute a Hue-Saturation for each given image
void	calcHSVHist (const std::vector< cv::Mat > &src, cv::MatND &histogram)
	calcHSVHist compute and return Hue-Saturation histogram of a given set of images
void	dctNormalization (const Image &img, Image &normalizedImg, int coefficientsToCancel, const ImageRoi &roi=ImageRoi(0, 0, 0, 0))
	illumination normalization using the discrete cosine transform (DCT).
void	dctNormalization (const cv::Mat &img, cv::Mat &normalizedImg, int coefficientsToCancel, const ImageRoi &roi=ImageRoi(0, 0, 0, 0))
void	getConnectedComponents (const cv::Mat &binaryImage, std::vector< std::vector< cv::Point2i > > &components, std::vector< cv::Rect > &boundingBoxes)
	getConnectedComponents finds connected components in the given binary image
void	getLab (const Image &img, Image &L, Image &a, Image &b)
	return the Lab components of the given image
cv::Mat	histogramImage (const cv::MatND &hist)
void	setLab (const Image &L, const Image &a, const Image &b, Image &img)
	build up a new image from the three Lab components provided.
void	showHist (const cv::MatND &hist, bool waitKey=true)
	showHist visualize a Hue-Saturation histogram

Detailed Description

Author:: Bence Magyar; Jordi Pages

Function Documentation

void pal_vision_util::backProject	(	const cv::Mat &	image,
		const cv::MatND &	hist,
		int	threshold,
		cv::Mat &	result,
		int	dilateIterations = `0`,
		int	dilateSize = `3`,
		int	erodeIterations = `0`,
		int	erodeSize = `3`
	)

backProject generate a binary image resulting of thresholding the per-pixel backprojection of a H-S histogram to a color image

Parameters:

image	the input BGR image
hist	the input H-S histogram
result	the resulting 1 channel 8 bit image corresponding so that a pixel is 255 if the result of its back-projection is > threshold, otherwise the pixel is set to 0.

Definition at line 146 of file histogram.cpp.

void pal_vision_util::calcHSVHist	(	const cv::Mat &	src,
		cv::MatND &	histogram
	)

calcHSVHist compute and return a Hue-Saturation histogram of a given image

Parameters:

src
histogram

Definition at line 47 of file histogram.cpp.

void pal_vision_util::calcHSVHist	(	const std::vector< cv::Mat > &	src,
		std::vector< cv::MatND > &	histograms
	)

calcHSVHist compute a Hue-Saturation for each given image

Parameters:

src
histogram

Definition at line 71 of file histogram.cpp.

void pal_vision_util::calcHSVHist	(	const std::vector< cv::Mat > &	src,
		cv::MatND &	histogram
	)

calcHSVHist compute and return Hue-Saturation histogram of a given set of images

Parameters:

src
histograms

Definition at line 83 of file histogram.cpp.

void pal_vision_util::dctNormalization	(	const Image &	img,
		Image &	normalizedImg,
		int	coefficientsToCancel,
		const ImageRoi &	roi = `ImageRoi(0,0,0,0)`
	)

illumination normalization using the discrete cosine transform (DCT).

Parameters:

[in]	img	input image
[out]	normalizedImg	resulting normalized image
[in]	coefficientsToCancel	number of DCT coefficients that will be truncated
[in]	ImageRoi	optional. Image region in which normalization will be carried on.

Definition at line 324 of file image_processing.cpp.

void pal_vision_util::dctNormalization	(	const cv::Mat &	img,
		cv::Mat &	normalizedImg,
		int	coefficientsToCancel,
		const ImageRoi &	roi = `ImageRoi(0,0,0,0)`
	)

See also:: dctNormalization(). Overloaded function accepting OpenCV C++ image as input and output.

Definition at line 458 of file image_processing.cpp.

void pal_vision_util::getConnectedComponents	(	const cv::Mat &	binaryImage,
		std::vector< std::vector< cv::Point2i > > &	components,
		std::vector< cv::Rect > &	boundingBoxes
	)

getConnectedComponents finds connected components in the given binary image

Parameters:

[in]	binaryImage.	Pixels set at 0 will be considered background, otherwise foreground.
[out]	components	for every connected component found this vector contains a vector of pixel coordinates that belong to the component (non black pixels).
[out]	boundingBoxes	bounding rectangle of every connected component

Definition at line 45 of file image_processing.cpp.

void pal_vision_util::getLab	(	const Image &	img,
		Image &	L,
		Image &	a,
		Image &	b
	)

return the Lab components of the given image

Definition at line 293 of file image_processing.cpp.

cv::Mat pal_vision_util::histogramImage ( const cv::MatND & hist )

Definition at line 112 of file histogram.cpp.

void pal_vision_util::setLab	(	const Image &	L,
		const Image &	a,
		const Image &	b,
		Image &	img
	)

build up a new image from the three Lab components provided.

Definition at line 311 of file image_processing.cpp.

void pal_vision_util::showHist	(	const cv::MatND &	hist,
		bool	waitKey = `true`
	)

showHist visualize a Hue-Saturation histogram

Parameters:

hist
waitKey	if true, the user has to press a key on the image to continue

Definition at line 136 of file histogram.cpp.

Classes

Functions

Detailed Description

Function Documentation