Image Statistics

Collaboration diagram for Image Statistics:

Files
file	stat.h

Functions
size_t **	icv_hist (icv_image_t *img, size_t n_bins)
double *	icv_min (icv_image_t *img)
double *	icv_mean (icv_image_t *img)
double *	icv_sum (icv_image_t *img)
double *	icv_max (icv_image_t *img)
int *	icv_mode (icv_image_t *img, size_t **bins, size_t n_bins)
int *	icv_median (icv_image_t *img, size_t **bins, size_t n_bins)
double *	icv_skew (icv_image_t *img, size_t **bins, size_t n_bins)
double *	icv_var (icv_image_t *img, size_t **bins, size_t n_bins)

Detailed Description

Image statistics and histogram routines.

Function Documentation

icv_hist()

size_t ** icv_hist	(	icv_image_t *	img,
		size_t	n_bins
	)

This function calculates the histogram of different channels separately.

Parameters

img	Image of which histogram is to found.
n_bins	number of bins required.

Returns

Histogram of size_t type array. This 2-dimension array is of size c X n_bins where c is the channels in the image.

icv_min()

double * icv_min

(

icv_image_t *

img

)

Finds the minimum value in each channel of the image.

Returns

a double array of size channels. Each element contains min value of the channel.

e.g. min = icv_min(bif); min[0] gives the minimum value of all the pixels in first bin. and so on.

icv_mean()

double * icv_mean

(

icv_image_t *

img

)

Finds the average value in each channel of the image.

Returns

a double array of size channels. Each elements contains average value of the channel.

e.g. mean = icv_mean(bif); mean[0] gives the average value of all the pixels in first channel and so on.

icv_sum()

double * icv_sum

(

icv_image_t *

img

)

Finds the sum of all the pixel values for each channel of the image

Returns

a double array of size channels. Each element contains sum value of the channel.

e.g. sum = icv_sum(bif); sum[0] gives the sum of all the pixels in first channel and so on.

icv_max()

double * icv_max

(

icv_image_t *

img

)

Finds the max value in each channel of the image.

Returns

a double array of size channels. Each element contains max value of the channel.

e.g. max = icv_max(bif); max[0] gives the maximum value of all the pixels in first bin. and so on.

icv_mode()

int * icv_mode	(	icv_image_t *	img,
		size_t **	bins,
		size_t	n_bins
	)

Calculates mode of the values of each channel. Mode value are calculated for quantified data which is sent as bins(histogram Information). For any image mode is a 'c' length array where c is the number of channels.

To calculate the mode of an icv_image, a default call is as follows icv_mode(img, icv_hist(img, n_bins), n_bins);

This call first calculates the histogram of the image. then finds the mode values from histogram of each channel.

icv_median()

int * icv_median	(	icv_image_t *	img,
		size_t **	bins,
		size_t	n_bins
	)

Calculates median of the values of each channel. Median value are calculated for quantified data which is sent as bins(histogram information). For any image mode is a 'c' length array, where c is the number of channels.

To calculate the median of an icv_image, a default call is as follows : icv_median(img, icv_hist(img, n_bins), n_bins);

This call first calculates the histogram of the image. then finds the mode values from histogram of each channel.

icv_skew()

double * icv_skew	(	icv_image_t *	img,
		size_t **	bins,
		size_t	n_bins
	)

Calculates the skewness in data.

To calculate the skewness in an icv_image, a default call is as follows : icv_skew(img, icv_hist(img, n_bins), n_bins);

Returns

c length double array where c is the number of channels in the img

icv_var()

double * icv_var	(	icv_image_t *	img,
		size_t **	bins,
		size_t	n_bins
	)

Calculates the variance in data.

To calculate the variance in an icv_image, a default call is as follows : icv_variance(img, icv_hist(img, n_bins), n_bins);

Returns

c length double array where c is the number of channels in the img