README
# rescribe.xyz/preproc package This package contains various image processing methods which are useful for preprocessing page images for OCR. It also contains several commands in the cmd/ directory which can be used to preprocess images directly. This is a Go package, and can be installed in the standard go way, by running `go get rescribe.xyz/preproc/...` and documentation can be read with the `go doc` command or online at <https://pkg.go.dev/rescribe.xyz/preproc>. If you just want to install and use the commands, you can get the package with `git clone https://git.rescribe.xyz/preproc`, and then install them with `go install ./...` from within the `preproc` directory. ## Commands There are several commands in the cmd/ directory which are useful in their own right as well as serving as examples of using the package. - binarize : binarises an image using the sauvola algorithm - pggraph : creates a graph showing the proportion of black pixels for slices through an image - preproc : binarises and wipes an image - preprocmulti : binarises and wipes an image with multiple binarisation ksize values - wipe : wipes sections of an image that are outside an area detected as content ## Bugs The integral image operations don't produce exactly the same result as their non-integral image counterparts. The difference is small enough that it has little effect on the output images, but it ought to be identical. ## Contributions Any and all comments, bug reports, patches or pull requests would be very welcomely received. Please email them to <nick@rescribe.xyz>. ## License This package is licensed under the GPLv3. See the LICENSE file for more details.
Documentation
Overview ¶
preproc contains various image processing methods which are useful for preprocessing page images for OCR. It contains both library functions to incorporate into your own projects and standalone tools which can be used directly.
Index ¶
- func BinToZeroInv(bin *image.Gray, orig *image.RGBA) (*image.RGBA, error)
- func IntegralSauvola(img image.Image, ksize float64, windowsize int) *image.Gray
- func PreCalcedSauvola(intImg integral.Image, intSqImg integral.SqImage, img image.Image, ...) *image.Gray
- func PreProcMulti(inPath string, ksizes []float64, binType string, binWsize int, wipe bool, ...) ([]string, error)
- func ProportionSlice(i SummableImage, x int, width int) float64
- func Sauvola(img image.Image, ksize float64, windowsize int) *image.Gray
- func VWipe(img *image.Gray, wsize int, thresh float64, min int) *image.Gray
- func Wipe(img *image.Gray, wsize int, thresh float64, min int) *image.Gray
- func WipeFile(inPath string, outPath string, hwsize int, hthresh float64, hmin int, ...) error
- type SummableImage
Constants ¶
Variables ¶
Functions ¶
func BinToZeroInv ¶
BinToZeroInv converts a binary thresholded image to a zero inverse binary thresholded image
func IntegralSauvola ¶
Implements Sauvola's algorithm using Integral Images, see paper "Efficient Implementation of Local Adaptive Thresholding Techniques Using Integral Images" and https://stackoverflow.com/questions/13110733/computing-image-integral
func PreCalcedSauvola ¶
func PreCalcedSauvola(intImg integral.Image, intSqImg integral.SqImage, img image.Image, ksize float64, windowsize int) *image.Gray
PreCalcedSauvola Implements Sauvola's algorithm using precalculated Integral Images
func PreProcMulti ¶
func PreProcMulti(inPath string, ksizes []float64, binType string, binWsize int, wipe bool, wipeWsize int, wipeMinWidthPerc int, vWipeWsize int, wipeMinHeightPerc int) ([]string, error)
PreProcMulti binarizes and preprocesses an image with multiple binarisation levels. inPath: Path of input image. ksizes: Slice of k values to pass to Sauvola algorithm binType: Type of binarization threshold. binary or zeroinv are currently implemented. binWsize: Window size for sauvola binarization algorithm. Set automatically based on resolution if 0. wipe: Whether to wipe (clear sides) the image wipeWsize: Window size for wiping algorithm wipeMinWidthPerc: Minimum percentage of the image width for the content width calculation to be considered valid vWipeWsize: Window size for vertical wiping algorithm wipeMinHeightPerc: Minimum percentage of the image height for the content height calculation to be considered valid
func ProportionSlice ¶
func ProportionSlice(i SummableImage, x int, width int) float64
ProportionSlice returns the proportion of black pixels in a vertical slice of an image starting at x, width pixels wide.
func Sauvola ¶
Implements Sauvola's algorithm for text binarization, see paper "Adaptive document image binarization" (2000)
func VWipe ¶
VWipe fills the sections of image which fall outside the vertical content area with white, providing the content area is above min %
func Wipe ¶
Wipe fills the sections of image which fall outside the content area with white, providing the content area is above min %
func WipeFile ¶
func WipeFile(inPath string, outPath string, hwsize int, hthresh float64, hmin int, vwsize int, vthresh float64, vmin int) error
WipeFile wipes an image file, filling the sections of the image which fall outside the content area with white, providing the content area is above min %. inPath: path of the input image. outPath: path to save the output image. hwsize: window size (width) for horizontal wipe algorithm. hthresh: threshold for horizontal wipe algorithm. hmin: minimum % of content area width to consider valid. vwsize: window size (height) for vertical wipe algorithm. vthresh: threshold for vertical wipe algorithm. vmin: minimum % of content area height to consider valid.
Types ¶
Directories
Path | Synopsis |
---|---|
cmd/binarize | binarize does fast Integral Image sauvola binarisation on an image |
cmd/pggraph | pggraph creates a graph showing the proportion of black pixels for slices through a binarised image. |
cmd/preproc | preproc runs binarisation and wipe preprocessing on an image |
cmd/preprocmulti | preprocmulti runs binarisation with a variety of different binarisation levels, preprocessing and saving each version |
cmd/wipe | wipe wipes sections of an image which are outside of an automatically determined content area |