Image::Leptonica::Func::kernel
version 0.04
kernel.c
kernel.c Basic operations on kernels for image convolution Create/destroy/copy L_KERNEL *kernelCreate() void kernelDestroy() L_KERNEL *kernelCopy() Accessors: l_int32 kernelGetElement() l_int32 kernelSetElement() l_int32 kernelGetParameters() l_int32 kernelSetOrigin() l_int32 kernelGetSum() l_int32 kernelGetMinMax() Normalize/invert L_KERNEL *kernelNormalize() L_KERNEL *kernelInvert() Helper function l_float32 **create2dFloatArray() Serialized I/O L_KERNEL *kernelRead() L_KERNEL *kernelReadStream() l_int32 kernelWrite() l_int32 kernelWriteStream() Making a kernel from a compiled string L_KERNEL *kernelCreateFromString() Making a kernel from a simple file format L_KERNEL *kernelCreateFromFile() Making a kernel from a Pix L_KERNEL *kernelCreateFromPix() Display a kernel in a pix PIX *kernelDisplayInPix() Parse string to extract numbers NUMA *parseStringForNumbers() Simple parametric kernels L_KERNEL *makeFlatKernel() L_KERNEL *makeGaussianKernel() L_KERNEL *makeGaussianKernelSep() L_KERNEL *makeDoGKernel()
l_float32 ** create2dFloatArray ( l_int32 sy, l_int32 sx )
create2dFloatArray() Input: sy (rows == height) sx (columns == width) Return: doubly indexed array (i.e., an array of sy row pointers, each of which points to an array of sx floats) Notes: (1) The array[sy][sx] is indexed in standard "matrix notation", with the row index first.
L_KERNEL * kernelCopy ( L_KERNEL *kels )
kernelCopy() Input: kels (source kernel) Return: keld (copy of kels), or null on error
L_KERNEL * kernelCreate ( l_int32 height, l_int32 width )
kernelCreate() Input: height, width Return: kernel, or null on error Notes: (1) kernelCreate() initializes all values to 0. (2) After this call, (cy,cx) and nonzero data values must be assigned.
L_KERNEL * kernelCreateFromFile ( const char *filename )
kernelCreateFromFile() Input: filename Return: kernel, or null on error Notes: (1) The file contains, in the following order: - Any number of comment lines starting with '#' are ignored - The height and width of the kernel - The y and x values of the kernel origin - The kernel data, formatted as lines of numbers (integers or floats) for the kernel values in row-major order, and with no other punctuation. (Note: this differs from kernelCreateFromString(), where each line must begin and end with a double-quote to tell the compiler it's part of a string.) - The kernel specification ends when a blank line, a comment line, or the end of file is reached. (2) All lines must be left-justified. (3) See kernelCreateFromString() for a description of the string format for the kernel data. As an example, here are the lines of a valid kernel description file In the file, all lines are left-justified: # small 3x3 kernel 3 3 1 1 25.5 51 24.3 70.2 146.3 73.4 20 50.9 18.4
L_KERNEL * kernelCreateFromPix ( PIX *pix, l_int32 cy, l_int32 cx )
kernelCreateFromPix() Input: pix cy, cx (origin of kernel) Return: kernel, or null on error Notes: (1) The origin must be positive and within the dimensions of the pix.
L_KERNEL * kernelCreateFromString ( l_int32 h, l_int32 w, l_int32 cy, l_int32 cx, const char *kdata )
kernelCreateFromString() Input: height, width cy, cx (origin) kdata Return: kernel of the given size, or null on error Notes: (1) The data is an array of chars, in row-major order, giving space separated integers in the range [-255 ... 255]. (2) The only other formatting limitation is that you must leave space between the last number in each row and the double-quote. If possible, it's also nice to have each line in the string represent a line in the kernel; e.g., static const char *kdata = " 20 50 20 " " 70 140 70 " " 20 50 20 ";
void kernelDestroy ( L_KERNEL **pkel )
kernelDestroy() Input: &kel (<to be nulled>) Return: void
PIX * kernelDisplayInPix ( L_KERNEL *kel, l_int32 size, l_int32 gthick )
kernelDisplayInPix() Input: kernel size (of grid interiors; odd; either 1 or a minimum size of 17 is enforced) gthick (grid thickness; either 0 or a minimum size of 2 is enforced) Return: pix (display of kernel), or null on error Notes: (1) This gives a visual representation of a kernel. (2) There are two modes of display: (a) Grid lines of minimum width 2, surrounding regions representing kernel elements of minimum size 17, with a "plus" mark at the kernel origin, or (b) A pix without grid lines and using 1 pixel per kernel element. (3) For both cases, the kernel absolute value is displayed, normalized such that the maximum absolute value is 255. (4) Large 2D separable kernels should be used for convolution with two 1D kernels. However, for the bilateral filter, the computation time is independent of the size of the 2D content kernel.
l_int32 kernelGetElement ( L_KERNEL *kel, l_int32 row, l_int32 col, l_float32 *pval )
kernelGetElement() Input: kel row col &val Return: 0 if OK; 1 on error
l_int32 kernelGetMinMax ( L_KERNEL *kel, l_float32 *pmin, l_float32 *pmax )
kernelGetMinMax() Input: kernel &min (<optional return> minimum value) &max (<optional return> maximum value) Return: 0 if OK, 1 on error
l_int32 kernelGetParameters ( L_KERNEL *kel, l_int32 *psy, l_int32 *psx, l_int32 *pcy, l_int32 *pcx )
kernelGetParameters() Input: kernel &sy, &sx, &cy, &cx (<optional return>; each can be null) Return: 0 if OK, 1 on error
l_int32 kernelGetSum ( L_KERNEL *kel, l_float32 *psum )
kernelGetSum() Input: kernel &sum (<return> sum of all kernel values) Return: 0 if OK, 1 on error
L_KERNEL * kernelInvert ( L_KERNEL *kels )
kernelInvert() Input: kels (source kel, to be inverted) Return: keld (spatially inverted, about the origin), or null on error Notes: (1) For convolution, the kernel is spatially inverted before a "correlation" operation is done between the kernel and the image.
L_KERNEL * kernelNormalize ( L_KERNEL *kels, l_float32 normsum )
kernelNormalize() Input: kels (source kel, to be normalized) normsum (desired sum of elements in keld) Return: keld (normalized version of kels), or null on error or if sum of elements is very close to 0) Notes: (1) If the sum of kernel elements is close to 0, do not try to calculate the normalized kernel. Instead, return a copy of the input kernel, with a warning.
L_KERNEL * kernelRead ( const char *fname )
kernelRead() Input: filename Return: kernel, or null on error
L_KERNEL * kernelReadStream ( FILE *fp )
kernelReadStream() Input: stream Return: kernel, or null on error
l_int32 kernelSetElement ( L_KERNEL *kel, l_int32 row, l_int32 col, l_float32 val )
kernelSetElement() Input: kernel row col val Return: 0 if OK; 1 on error
l_int32 kernelSetOrigin ( L_KERNEL *kel, l_int32 cy, l_int32 cx )
kernelSetOrigin() Input: kernel cy, cx Return: 0 if OK; 1 on error
l_int32 kernelWrite ( const char *fname, L_KERNEL *kel )
kernelWrite() Input: fname (output file) kernel Return: 0 if OK, 1 on error
l_int32 kernelWriteStream ( FILE *fp, L_KERNEL *kel )
kernelWriteStream() Input: stream kel Return: 0 if OK, 1 on error
L_KERNEL * makeDoGKernel ( l_int32 halfheight, l_int32 halfwidth, l_float32 stdev, l_float32 ratio )
makeDoGKernel() Input: halfheight, halfwidth (sx = 2 * halfwidth + 1, etc) stdev (standard deviation of narrower gaussian) ratio (of stdev for wide filter to stdev for narrow one) Return: kernel, or null on error Notes: (1) The DoG (difference of gaussians) is a wavelet mother function with null total sum. By subtracting two blurred versions of the image, it acts as a bandpass filter for frequencies passed by the narrow gaussian but stopped by the wide one.See: http://en.wikipedia.org/wiki/Difference_of_Gaussians (2) The kernel size (sx, sy) = (2 * halfwidth + 1, 2 * halfheight + 1). (3) The kernel center (cx, cy) = (halfwidth, halfheight). (4) The halfwidth and halfheight are typically equal, and are typically several times larger than the standard deviation. (5) The ratio is the ratio of standard deviations of the wide to narrow gaussian. It must be >= 1.0; 1.0 is a no-op. (6) Because the kernel is a null sum, it must be invoked without normalization in pixConvolve().
L_KERNEL * makeFlatKernel ( l_int32 height, l_int32 width, l_int32 cy, l_int32 cx )
makeFlatKernel() Input: height, width cy, cx (origin of kernel) Return: kernel, or null on error Notes: (1) This is the same low-pass filtering kernel that is used in the block convolution functions. (2) The kernel origin (@cy, @cx) is typically placed as near the center of the kernel as possible. If height and width are odd, then using cy = height / 2 and cx = width / 2 places the origin at the exact center. (3) This returns a normalized kernel.
L_KERNEL * makeGaussianKernel ( l_int32 halfheight, l_int32 halfwidth, l_float32 stdev, l_float32 max )
makeGaussianKernel() Input: halfheight, halfwidth (sx = 2 * halfwidth + 1, etc) stdev (standard deviation) max (value at (cx,cy)) Return: kernel, or null on error Notes: (1) The kernel size (sx, sy) = (2 * halfwidth + 1, 2 * halfheight + 1). (2) The kernel center (cx, cy) = (halfwidth, halfheight). (3) The halfwidth and halfheight are typically equal, and are typically several times larger than the standard deviation. (4) If pixConvolve() is invoked with normalization (the sum of kernel elements = 1.0), use 1.0 for max (or any number that's not too small or too large).
l_int32 makeGaussianKernelSep ( l_int32 halfheight, l_int32 halfwidth, l_float32 stdev, l_float32 max, L_KERNEL **pkelx, L_KERNEL **pkely )
makeGaussianKernelSep() Input: halfheight, halfwidth (sx = 2 * halfwidth + 1, etc) stdev (standard deviation) max (value at (cx,cy)) &kelx (<return> x part of kernel) &kely (<return> y part of kernel) Return: 0 if OK, 1 on error Notes: (1) See makeGaussianKernel() for description of input parameters. (2) These kernels are constructed so that the result of both normalized and un-normalized convolution will be the same as when convolving with pixConvolve() using the full kernel. (3) The trick for the un-normalized convolution is to have the product of the two kernel elemets at (cx,cy) be equal to max, not max**2. That's why the max for kely is 1.0. If instead we use sqrt(max) for both, the results are slightly less accurate, when compared to using the full kernel in makeGaussianKernel().
NUMA * parseStringForNumbers ( const char *str, const char *seps )
parseStringForNumbers() Input: string (containing numbers; not changed) seps (string of characters that can be used between ints) Return: numa (of numbers found), or null on error Note: (1) The numbers can be ints or floats.
Zakariyya Mughal <zmughal@cpan.org>
This software is copyright (c) 2014 by Zakariyya Mughal.
This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.
To install Image::Leptonica, copy and paste the appropriate command in to your terminal.
cpanm
cpanm Image::Leptonica
CPAN shell
perl -MCPAN -e shell install Image::Leptonica
For more information on module installation, please visit the detailed CPAN module installation guide.