Package net.sourceforge.lept4j
Class L_Recog
- java.lang.Object
-
- com.sun.jna.Structure
-
- net.sourceforge.lept4j.L_Recog
-
- Direct Known Subclasses:
L_Recog.ByReference,L_Recog.ByValue
public class L_Recog extends com.sun.jna.Structurerecog.h
This is a simple utility for training and recognizing individual
machine-printed text characters. It is designed to be adapted
to a particular set of character images; e.g., from a book.
There are two methods of training the recognizer. In the most
simple, a set of bitmaps has been labeled by some means, such
a generic OCR program. This is input either one template at a time
or as a pixa of templates, to a function that creates a recog.
If in a pixa, the text string label must be embedded in the
text field of each pix.
If labeled data is not available, we start with a bootstrap
recognizer (BSR) that has labeled data from a variety of sources.
These images are scaled, typically to a fixed height, and then
fed similarly scaled unlabeled images from the source (e.g., book),
and the BSR attempts to identify them. All images that have
a high enough correlation score with one of the templates in the
BSR are emitted in a pixa, which now holds unscaled and labeled
templates from the source. This is the generator for a book adapted
recognizer (BAR).
The pixa should always be thought of as the primary structure.
It is the generator for the recog, because a recog is built
from a pixa of unscaled images.
New image templates can be added to a recog as long as it is
in training mode. Once training is finished, to add templates
it is necessary to extract the generating pixa, add templates
to that pixa, and make a new recog. Similarly, we do not
join two recog; instead, we simply join their generating pixa,
and make a recog from that.
To remove outliers from a pixa of labeled pix, make a recog,
determine the outliers, and generate a new pixa with the
outliers removed. The outliers are determined by building
special templates for each character set that are scaled averages
of the individual templates. Then a correlation score is found
between each template and the averaged templates. There are
two implementations; outliers are determined as either:
(1) a template having a correlation score with its class average
that is below a threshold, or
(2) a template having a correlation score with its class average
that is smaller than the correlation score with the average
of another class.
Outliers are removed from the generating pixa. Scaled averaging
is only performed for determining outliers and for splitting
characters; it is never used in a trained recognizer for identifying
unlabeled samples.
Two methods using averaged templates are provided for splitting
touching characters:
(1) greedy matching
(2) document image decoding (DID)
The DID method is the default. It is about 5x faster and
possibly more accurate.
Once a BAR has been made, unlabeled sample images are identified
by finding the individual template in the BAR with highest
correlation. The input images and images in the BAR can be
represented in two ways:
(1) as scanned, binarized to 1 bpp
(2) as a width-normalized outline formed by thinning to a
skeleton and then dilating by a fixed amount.
The recog can be serialized to file and read back. The serialized
version holds the templates used for correlation (which may have
been modified by scaling and turning into lines from the unscaled
templates), plus, for arbitrary character sets, the UTF8
representation and the lookup table mapping from the character
representation to index.
Why do we not use averaged templates for recognition?
Letterforms can take on significantly different shapes (eg.,
the letters 'a' and 'g'), and it makes no sense to average these.
The previous version of this utility allowed multiple recognizers
to exist, but this is an unnecessary complication if recognition
is done on all samples instead of on averages.
native declaration : recog.h:126
This file was autogenerated by JNAerator,
a tool written by Olivier Chafik that uses a few opensource projects..
For help, please visit NativeLibs4Java or JNA.
-
-
Nested Class Summary
Nested Classes Modifier and Type Class Description static classL_Recog.ByReferencestatic classL_Recog.ByValue
-
Field Summary
Fields Modifier and Type Field Description intave_doneset to 1 when averaged bitmaps are made
C type : l_int32L_Bmf.ByReferencebmfbmf fonts
C type : L_Bmf*intbmf_sizefont size of bmf; default is 6 pt
C type : l_int32com.sun.jna.ptr.IntByReferencecenttabtable for finding centroids
C type : l_int32*intcharset_sizeexpected number of classes in charset
C type : l_int32intcharset_typeone of L_ARABIC_NUMERALS, etc.
C type : l_int32L_Rdid.ByReferencedidtemp data used for image decoding
C type : L_Rdid*L_Dna.ByReferencedna_tocharindex-to-char lut for arbitrary charset
C type : L_Dna*intlinewuse a value > 0 to convert the bitmap
C type : l_int32floatmax_ht_ratiomax of max/min template height ratio
C type : l_float32intmax_splithmax component height kept in splitting
C type : l_int32floatmax_wh_ratiomax width/height ratio to split
C type : l_float32intmaxarraysizeinitialize container arrays to this
C type : l_int32intmaxheight_umax height averaged unscaled templates
C type : l_int32intmaxwidthmax width averaged scaled templates
C type : l_int32intmaxwidth_umax width averaged unscaled templates
C type : l_int32intmaxyshiftvertical jiggle on nominal centroid
C type : l_int32intmin_nopadmin number of samples without padding
C type : l_int32intmin_splitwmin component width kept in splitting
C type : l_int32intminheight_umin height averaged unscaled templates
C type : l_int32intminwidthmin width averaged scaled templates
C type : l_int32intminwidth_umin width averaged unscaled templates
C type : l_int32Numaa.ByReferencenaasumarea of all (scaled) templates
C type : Numaa*Numaa.ByReferencenaasum_uarea of all unscaled templates
C type : Numaa*Numa.ByReferencenasumarea of (scaled) averaged templates
C type : Numa*Numa.ByReferencenasum_uarea of unscaled averaged templates
C type : Numa*intnum_samplesnumber of training samples
C type : l_int32Pixa.ByReferencepixaaveraged (scaled) templates per class
C type : Pixa*Pixa.ByReferencepixa_idinput images for identifying
C type : Pixa*Pixa.ByReferencepixa_trall input training images
C type : Pixa*Pixa.ByReferencepixa_uaveraged unscaled templates per class
C type : Pixa*Pixaa.ByReferencepixaaall (scaled) templates for each class
C type : Pixaa*Pixaa.ByReferencepixaa_uall unscaled templates for each class
C type : Pixaa*Pixa.ByReferencepixadb_aveunscaled and scaled averaged bitmaps
C type : Pixa*Pixa.ByReferencepixadb_bootdebug: bootstrap training results
C type : Pixa*Pixa.ByReferencepixadb_splitdebug: splitting results
C type : Pixa*Pix.ByReferencepixdb_avedebug: best match of input against ave.
C type : Pix*Pix.ByReferencepixdb_rangedebug: best matches within range
C type : Pix*Pta.ByReferenceptacentroids of (scaled) ave.Pta.ByReferencepta_ucentroids of unscaled ave.Ptaa.ByReferenceptaacentroids of all (scaledl) templates
C type : Ptaa*Ptaa.ByReferenceptaa_ucentroids of all unscaled templates
C type : Ptaa*L_Rch.ByReferencerchtemp data used for holding best char
C type : L_Rch*L_Rcha.ByReferencerchatemp data used for array of best chars
C type : L_Rcha*Sarray.ByReferencesa_texttext array for arbitrary charset
C type : Sarray*intscalehscale all examples to this height;
C type : l_int32intscalewscale all examples to this width;
C type : l_int32intsetsizesize of character set
C type : l_int32com.sun.jna.ptr.IntByReferencesumtabtable for finding pixel sums
C type : l_int32*inttempl_usetemplate use: use either the average
C type : l_int32intthresholdfor binarizing if depth > 1
C type : l_int32inttrain_doneset to 1 when training is complete or
C type : l_int32
-
Method Summary
Modifier and Type Method Description protected java.util.List<java.lang.String>getFieldOrder()Gets this Structure's field names in their proper order.-
Methods inherited from class com.sun.jna.Structure
allocateMemory, allocateMemory, autoAllocate, autoRead, autoRead, autoWrite, autoWrite, cacheTypeInfo, calculateSize, clear, createFieldsOrder, createFieldsOrder, createFieldsOrder, createFieldsOrder, dataEquals, dataEquals, ensureAllocated, equals, fieldOffset, getAutoRead, getAutoWrite, getFieldList, getFields, getNativeAlignment, getNativeSize, getNativeSize, getPointer, getStringEncoding, getStructAlignment, hashCode, newInstance, newInstance, read, readField, readField, setAlignType, setAutoRead, setAutoSynch, setAutoWrite, setStringEncoding, size, sortFields, toArray, toArray, toString, toString, useMemory, useMemory, write, writeField, writeField, writeField
-
-
-
-
Field Detail
-
scalew
public int scalew
scale all examples to this width;
C type : l_int32
-
scaleh
public int scaleh
scale all examples to this height;
C type : l_int32
-
linew
public int linew
use a value > 0 to convert the bitmap
C type : l_int32
-
templ_use
public int templ_use
template use: use either the average
C type : l_int32
-
maxarraysize
public int maxarraysize
initialize container arrays to this
C type : l_int32
-
setsize
public int setsize
size of character set
C type : l_int32
-
threshold
public int threshold
for binarizing if depth > 1
C type : l_int32
-
maxyshift
public int maxyshift
vertical jiggle on nominal centroid
C type : l_int32
-
charset_type
public int charset_type
one of L_ARABIC_NUMERALS, etc.
C type : l_int32
-
charset_size
public int charset_size
expected number of classes in charset
C type : l_int32
-
min_nopad
public int min_nopad
min number of samples without padding
C type : l_int32
-
num_samples
public int num_samples
number of training samples
C type : l_int32
-
minwidth_u
public int minwidth_u
min width averaged unscaled templates
C type : l_int32
-
maxwidth_u
public int maxwidth_u
max width averaged unscaled templates
C type : l_int32
-
minheight_u
public int minheight_u
min height averaged unscaled templates
C type : l_int32
-
maxheight_u
public int maxheight_u
max height averaged unscaled templates
C type : l_int32
-
minwidth
public int minwidth
min width averaged scaled templates
C type : l_int32
-
maxwidth
public int maxwidth
max width averaged scaled templates
C type : l_int32
-
ave_done
public int ave_done
set to 1 when averaged bitmaps are made
C type : l_int32
-
train_done
public int train_done
set to 1 when training is complete or
C type : l_int32
-
max_wh_ratio
public float max_wh_ratio
max width/height ratio to split
C type : l_float32
-
max_ht_ratio
public float max_ht_ratio
max of max/min template height ratio
C type : l_float32
-
min_splitw
public int min_splitw
min component width kept in splitting
C type : l_int32
-
max_splith
public int max_splith
max component height kept in splitting
C type : l_int32
-
sa_text
public Sarray.ByReference sa_text
text array for arbitrary charset
C type : Sarray*
-
dna_tochar
public L_Dna.ByReference dna_tochar
index-to-char lut for arbitrary charset
C type : L_Dna*
-
centtab
public com.sun.jna.ptr.IntByReference centtab
table for finding centroids
C type : l_int32*
-
sumtab
public com.sun.jna.ptr.IntByReference sumtab
table for finding pixel sums
C type : l_int32*
-
pixaa_u
public Pixaa.ByReference pixaa_u
all unscaled templates for each class
C type : Pixaa*
-
ptaa_u
public Ptaa.ByReference ptaa_u
centroids of all unscaled templates
C type : Ptaa*
-
naasum_u
public Numaa.ByReference naasum_u
area of all unscaled templates
C type : Numaa*
-
pixaa
public Pixaa.ByReference pixaa
all (scaled) templates for each class
C type : Pixaa*
-
ptaa
public Ptaa.ByReference ptaa
centroids of all (scaledl) templates
C type : Ptaa*
-
naasum
public Numaa.ByReference naasum
area of all (scaled) templates
C type : Numaa*
-
pixa_u
public Pixa.ByReference pixa_u
averaged unscaled templates per class
C type : Pixa*
-
pta_u
public Pta.ByReference pta_u
centroids of unscaled ave. templates
C type : Pta*
-
nasum_u
public Numa.ByReference nasum_u
area of unscaled averaged templates
C type : Numa*
-
pixa
public Pixa.ByReference pixa
averaged (scaled) templates per class
C type : Pixa*
-
pta
public Pta.ByReference pta
centroids of (scaled) ave. templates
C type : Pta*
-
nasum
public Numa.ByReference nasum
area of (scaled) averaged templates
C type : Numa*
-
pixa_tr
public Pixa.ByReference pixa_tr
all input training images
C type : Pixa*
-
pixadb_ave
public Pixa.ByReference pixadb_ave
unscaled and scaled averaged bitmaps
C type : Pixa*
-
pixa_id
public Pixa.ByReference pixa_id
input images for identifying
C type : Pixa*
-
pixdb_ave
public Pix.ByReference pixdb_ave
debug: best match of input against ave.
C type : Pix*
-
pixdb_range
public Pix.ByReference pixdb_range
debug: best matches within range
C type : Pix*
-
pixadb_boot
public Pixa.ByReference pixadb_boot
debug: bootstrap training results
C type : Pixa*
-
pixadb_split
public Pixa.ByReference pixadb_split
debug: splitting results
C type : Pixa*
-
bmf
public L_Bmf.ByReference bmf
bmf fonts
C type : L_Bmf*
-
bmf_size
public int bmf_size
font size of bmf; default is 6 pt
C type : l_int32
-
did
public L_Rdid.ByReference did
temp data used for image decoding
C type : L_Rdid*
-
rch
public L_Rch.ByReference rch
temp data used for holding best char
C type : L_Rch*
-
rcha
public L_Rcha.ByReference rcha
temp data used for array of best chars
C type : L_Rcha*
-
-