public override void Charseg(ref Intarray outimage, Bytearray inimage) { int swidth = PGeti("swidth"); int sheight = PGeti("sheight"); Bytearray image = new Bytearray(); image.Copy(inimage); OcrRoutine.binarize_simple(image); OcrRoutine.Invert(image); outimage.Copy(image); if (swidth > 0 || sheight > 0) { Morph.binary_close_rect(image, swidth, sheight); } Intarray labels = new Intarray(); labels.Copy(image); ImgLabels.label_components(ref labels); for (int i = 0; i < outimage.Length1d(); i++) { if (outimage.At1d(i) > 0) { outimage.Put1d(i, SegmRoutine.cseg_pixel(labels.At1d(i))); } } SegmRoutine.make_line_segmentation_white(outimage); SegmRoutine.check_line_segmentation(outimage); }
public override void Charseg(ref Intarray outimage, Bytearray inarray) { Bytearray image = new Bytearray(); image.Copy(inarray); OcrRoutine.binarize_simple(image); OcrRoutine.Invert(image); outimage.Copy(image); Intarray labels = new Intarray(); labels.Copy(image); ImgLabels.label_components(ref labels); Narray <Rect> boxes = new Narray <Rect>(); ImgLabels.bounding_boxes(ref boxes, labels); Intarray equiv = new Intarray(boxes.Length()); for (int i = 0; i < boxes.Length(); i++) { equiv[i] = i; } for (int i = 1; i < boxes.Length(); i++) { Rect p = boxes[i]; for (int j = 1; j < boxes.Length(); j++) { if (i == j) { continue; } Rect q = boxes[j]; int x0 = Math.Max(p.x0, q.x0); int x1 = Math.Min(p.x1, q.x1); int iw = x1 - x0; if (iw <= 0) { continue; // no overlap } int ow = Math.Min(p.Width(), q.Width()); float frac = iw / (float)(ow); if (frac < 0.5f) { continue; // insufficient overlap } // printf("%d %d : %d %d : %g\n",i,j,iw,ow,frac); equiv.Put1d(Math.Max(i, j), Math.Min(i, j)); } } for (int i = 0; i < labels.Length(); i++) { labels.Put1d(i, equiv.At1d(labels.At1d(i))); } ImgLabels.renumber_labels(labels, 1); outimage.Move(labels); SegmRoutine.make_line_segmentation_white(outimage); SegmRoutine.check_line_segmentation(outimage); }
public override void Charseg(ref Intarray segmentation, Bytearray inraw) { Logger.Default.Image("segmenting", inraw); OcrRoutine.optional_check_background_is_lighter(inraw); Bytearray image = new Bytearray(); image.Copy(inraw); OcrRoutine.binarize_simple(image); OcrRoutine.Invert(image); segmenter.SetImage(image); segmenter.FindAllCuts(); segmenter.FindBestCuts(); Intarray seg = new Intarray(); seg.Copy(image); for (int r = 0; r < segmenter.bestcuts.Length(); r++) { int w = seg.Dim(0); int c = segmenter.bestcuts[r]; Narray <Point> cut = segmenter.cuts[c]; for (int y = 0; y < image.Dim(1); y++) { for (int i = -1; i <= 1; i++) { int x = cut[y].X; if (x < 1 || x >= w - 1) { continue; } seg[x + i, y] = 0; } } } ImgLabels.label_components(ref seg); // dshowr(seg,"YY"); dwait(); segmentation.Copy(image); ImgLabels.propagate_labels_to(ref segmentation, seg); SegmRoutine.line_segmentation_merge_small_components(ref segmentation, small_merge_threshold); SegmRoutine.line_segmentation_sort_x(segmentation); SegmRoutine.make_line_segmentation_white(segmentation); // set_line_number(segmentation, 1); Logger.Default.Image("resulting segmentation", segmentation); }
public override void Charseg(ref Intarray result_segmentation, Bytearray orig_image) { Bytearray image = new Bytearray(); image.Copy(orig_image); OcrRoutine.optional_check_background_is_lighter(image); OcrRoutine.binarize_simple(image); OcrRoutine.Invert(image); Intarray ccseg = new Intarray(); ccseg.Copy(image); ImgLabels.label_components(ref ccseg); base.Charseg(ref result_segmentation, orig_image); SegmRoutine.combine_segmentations(ref result_segmentation, ccseg); }
public static void erase_small_components(Floatarray input, float mins = 0.2f, float thresh = 0.25f) { // compute a thresholded image for component labeling float threshold = thresh * NarrayUtil.Max(input); Intarray components = new Intarray(); components.MakeLike(input); components.Fill(0); for (int i = 0; i < components.Length(); i++) { components[i] = (input[i] > threshold ? 1 : 0); } // compute the number of pixels in each component int n = ImgLabels.label_components(ref components); Intarray totals = new Intarray(n + 1); totals.Fill(0); for (int i = 0; i < components.Length(); i++) { totals[components[i]] = totals[components[i]] + 1; } totals[0] = 0; int biggest = NarrayUtil.ArgMax(totals); // erase small components float minsize = mins * totals[biggest]; Bytearray keep = new Bytearray(n + 1); float background = NarrayUtil.Min(input); for (int i = 0; i < keep.Length(); i++) { keep[i] = (byte)(totals[i] > minsize ? 1 : 0); } for (int i = 0; i < input.Length(); i++) { if (keep[components[i]] == 0) { input[i] = background; } } }
public void EstimateSpaceSize() { Intarray labels = new Intarray(); labels.Copy(segmentation); ImgLabels.label_components(ref labels); Narray <Rect> boxes = new Narray <Rect>(); ImgLabels.bounding_boxes(ref boxes, labels); Floatarray distances = new Floatarray(); distances.Resize(boxes.Length()); distances.Fill(99999f); for (int i = 1; i < boxes.Length(); i++) { Rect b = boxes[i]; for (int j = 1; j < boxes.Length(); j++) { Rect n = boxes[j]; int delta = n.x0 - b.x1; if (delta < 0) { continue; } if (delta >= distances[i]) { continue; } distances[i] = delta; } } float interchar = NarrayUtil.Fractile(distances, PGetf("space_fractile")); space_threshold = interchar * PGetf("space_multiplier"); // impose some reasonable upper and lower bounds float xheight = 10.0f; // FIXME space_threshold = Math.Max(space_threshold, PGetf("space_min") * xheight); space_threshold = Math.Min(space_threshold, PGetf("space_max") * xheight); }
public override void Charseg(ref Intarray segmentation, Bytearray image) { Bytearray timage = new Bytearray(); timage.Copy(image); //for (int i = 0; i < image.Length(); i++) image[i] = (byte)(image[i] > 0 ? 0 : 1); OcrRoutine.binarize_simple(timage); OcrRoutine.Invert(image); Skeleton.Thin(ref timage); //ImgIo.write_image_gray("_thinned.png", timage); ImgMisc.remove_singular_points(ref timage, 2); //ImgIo.write_image_gray("_segmented.png", timage); Intarray tsegmentation = new Intarray(); tsegmentation.Copy(timage); ImgLabels.label_components(ref tsegmentation); SegmRoutine.remove_small_components(tsegmentation, 4, 4); //ImgIo.write_image_packed("_labeled.png", tsegmentation); segmentation.Copy(image); ImgLabels.propagate_labels_to(ref segmentation, tsegmentation); //ImgIo.write_image_packed("_propagated.png", segmentation); }
public static void extract_holes(ref Bytearray holes, Bytearray binarized) { Intarray temp = new Intarray(); temp.Copy(binarized); NarrayUtil.Sub(255, temp); ImgLabels.label_components(ref temp); int background = -1; for (int i = 0; i < temp.Dim(0); i++) { if (temp[i, 0] != 0) { background = temp[i, 0]; break; } } holes.MakeLike(temp); holes.Fill((byte)0); if (background <= 0) { throw new Exception("extract_holes: background must be more 0"); } for (int i = 0; i < temp.Dim(0); i++) { for (int j = 0; j < temp.Dim(1); j++) { if (temp[i, j] > 0 && temp[i, j] != background) { holes[i, j] = 255; } } } /*fprintf(stderr, "segholes\n"); * dsection("segholes"); * dshow(holes, "y");*/ }
public static void remove_small_components <T>(Narray <T> bimage, int mw, int mh) { Intarray image = new Intarray(); image.Copy(bimage); ImgLabels.label_components(ref image); Narray <Rect> rects = new Narray <Rect>(); ImgLabels.bounding_boxes(ref rects, image); Bytearray good = new Bytearray(rects.Length()); for (int i = 0; i < good.Length(); i++) { good[i] = 1; } for (int i = 0; i < rects.Length(); i++) { if (rects[i].Width() < mw && rects[i].Height() < mh) { // printf("*** %d %d %d\n",i,rects[i].width(),rects[i].height()); good[i] = 0; } } for (int i = 0; i < image.Length1d(); i++) { if (good[image.At1d(i)] == 0) { image.Put1d(i, 0); } } for (int i = 0; i < image.Length1d(); i++) { if (image.At1d(i) == 0) { bimage.Put1d(i, default(T)); // default(T) - 0 } } }
public override void Charseg(ref Intarray segmentation, Bytearray inraw) { setParams(); //Logger.Default.Image("segmenting", inraw); int PADDING = 3; OcrRoutine.optional_check_background_is_lighter(inraw); Bytearray image = new Bytearray(); image.Copy(inraw); OcrRoutine.binarize_simple(image); OcrRoutine.Invert(image); SetImage(image); FindAllCuts(); FindBestCuts(); Intarray seg = new Intarray(); seg.MakeLike(image); seg.Fill(255); for (int r = 0; r < bestcuts.Length(); r++) { int w = seg.Dim(0); int c = bestcuts[r]; Narray <Point> cut = cuts[c]; for (int y = 0; y < image.Dim(1); y++) { for (int i = -1; i <= 1; i++) { int x = cut[y].X; if (x < 1 || x >= w - 1) { continue; } seg[x + i, y] = 0; } } } ImgLabels.label_components(ref seg); // dshowr(seg,"YY"); dwait(); segmentation.Copy(image); for (int i = 0; i < seg.Length1d(); i++) { if (segmentation.At1d(i) == 0) { seg.Put1d(i, 0); } } ImgLabels.propagate_labels_to(ref segmentation, seg); if (PGeti("component_segmentation") > 0) { Intarray ccseg = new Intarray(); ccseg.Copy(image); ImgLabels.label_components(ref ccseg); SegmRoutine.combine_segmentations(ref segmentation, ccseg); if (PGeti("fix_diacritics") > 0) { SegmRoutine.fix_diacritics(segmentation); } } #if false SegmRoutine.line_segmentation_merge_small_components(ref segmentation, small_merge_threshold); SegmRoutine.line_segmentation_sort_x(segmentation); #endif SegmRoutine.make_line_segmentation_white(segmentation); // set_line_number(segmentation, 1); //Logger.Default.Image("resulting segmentation", segmentation); }
protected void rescale(Floatarray v, Floatarray input) { if (input.Rank() != 2) { throw new Exception("CHECK_ARG: sub.Rank()==2"); } Floatarray sub = new Floatarray(); // find the largest connected component // and crop to its bounding box // (use a binary version of the character // to compute the bounding box) Intarray components = new Intarray(); float threshold = PGetf("threshold") * NarrayUtil.Max(input); Global.Debugf("biggestcc", "threshold {0}", threshold); components.MakeLike(input); components.Fill(0); for (int i = 0; i < components.Length(); i++) { components[i] = (input[i] > threshold ? 1 : 0); } int n = ImgLabels.label_components(ref components); Intarray totals = new Intarray(n + 1); totals.Fill(0); for (int i = 0; i < components.Length(); i++) { totals[components[i]]++; } totals[0] = 0; Narray <Rect> boxes = new Narray <Rect>(); ImgLabels.bounding_boxes(ref boxes, components); int biggest = NarrayUtil.ArgMax(totals); Rect r = boxes[biggest]; int pad = (int)(PGetf("pad") + 0.5f); r.PadBy(pad, pad); Global.Debugf("biggestcc", "({0}) {1}[{2}] :: {3} {4} {5} {6}", n, biggest, totals[biggest], r.x0, r.y0, r.x1, r.y1); // now perform normal feature extraction // (use the original grayscale input) sub = input; ImgMisc.Crop(sub, r); int csize = PGeti("csize"); float s = Math.Max(sub.Dim(0), sub.Dim(1)) / (float)csize; if (PGetf("noupscale") > 0 && s < 1.0f) { s = 1.0f; } float sig = s * PGetf("aa"); float dx = (csize * s - sub.Dim(0)) / 2f; float dy = (csize * s - sub.Dim(1)) / 2f; if (sig > 1e-3f) { Gauss.Gauss2d(sub, sig, sig); } v.Resize(csize, csize); v.Fill(0f); for (int i = 0; i < csize; i++) { for (int j = 0; j < csize; j++) { float x = i * s - dx; float y = j * s - dy; if (x < 0 || x >= sub.Dim(0)) { continue; } if (y < 0 || y >= sub.Dim(1)) { continue; } float value = ImgOps.bilin(sub, x, y); v[i, j] = value; } } /*Global.Debugf("biggestcc", "{0} {1} ({2}) -> {3} {4} ({5})", * sub.Dim(0), sub.Dim(1), NarrayUtil.Max(sub), * v.Dim(0), v.Dim(1), NarrayUtil.Max(v));*/ }
public List <List <float> > SpaceCosts(List <Candidate> candidates, Bytearray image) { /* * Given a list of character recognition candidates and their * classifications, and an image of the corresponding text line, * compute a list of pairs of costs for putting/not putting a space * after each of the candidate characters. * * The basic idea behind this simple algorithm is to try larger * and larger horizontal closing operations until most of the components * start having a "wide" aspect ratio; that's when characters have merged * into words. The remaining whitespace should be spaces. * * This is just a simple stopgap measure; it will be replaced with * trainable space modeling. */ int w = image.Dim(0); int h = image.Dim(1); Bytearray closed = new Bytearray(); int r; for (r = 0; r < maxrange; r++) { if (r > 0) { closed.Copy(image); Morph.binary_close_circle(closed, r); } else { closed.Copy(image); } Intarray labeled = new Intarray(); labeled.Copy(closed); ImgLabels.label_components(ref labeled); Narray <Rect> rects = new Narray <Rect>(); ImgLabels.bounding_boxes(ref rects, labeled); Floatarray aspects = new Floatarray(); for (int i = 0; i < rects.Length(); i++) { Rect rect = rects[i]; float aspect = rect.Aspect(); aspects.Push(aspect); } float maspect = NarrayUtil.Median(aspects); if (maspect >= this.aspect_threshold) { break; } } // close with a little bit of extra space closed.Copy(image); Morph.binary_close_circle(closed, r + 1); // compute the remaining aps //Morph.binary_dilate_circle(); // every character box that ends near a cap gets a space appended return(null); }