feat(ocr-pipeline): filter scan artifacts in content bounds and add margin regions
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Thin black lines (1-5px) at page edges from scanning were incorrectly
detected as content, shifting content bounds and creating spurious
IGNORE columns. This filters narrow projection runs (<1% of image
dimension) and introduces explicit margin_left/margin_right regions
for downstream page reconstruction.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
2026-03-02 15:29:18 +01:00
parent e718353d9f
commit 34ccdd5fd1
2 changed files with 247 additions and 18 deletions

View File

@@ -631,42 +631,70 @@ def create_layout_image(img: np.ndarray) -> np.ndarray:
# Stage 5: Layout Analysis (Projection Profiles)
# =============================================================================
def _filter_narrow_runs(mask: np.ndarray, min_width: int) -> np.ndarray:
"""Remove contiguous True-runs shorter than *min_width* from a 1-D bool mask."""
out = mask.copy()
n = len(out)
i = 0
while i < n:
if out[i]:
start = i
while i < n and out[i]:
i += 1
if (i - start) < min_width:
out[start:i] = False
else:
i += 1
return out
def _find_content_bounds(inv: np.ndarray) -> Tuple[int, int, int, int]:
"""Find the bounding box of actual text content (excluding page margins).
Scan artefacts (thin black lines at page edges) are filtered out by
discarding contiguous projection runs narrower than 1 % of the image
dimension (min 5 px).
Returns:
Tuple of (left_x, right_x, top_y, bottom_y).
"""
h, w = inv.shape[:2]
threshold = 0.005
# Horizontal projection for top/bottom
# --- Horizontal projection for top/bottom ---
h_proj = np.sum(inv, axis=1).astype(float) / (w * 255)
h_mask = h_proj > threshold
min_h_run = max(5, h // 100)
h_mask = _filter_narrow_runs(h_mask, min_h_run)
top_y = 0
for y in range(h):
if h_proj[y] > 0.005:
if h_mask[y]:
top_y = max(0, y - 5)
break
bottom_y = h
for y in range(h - 1, 0, -1):
if h_proj[y] > 0.005:
if h_mask[y]:
bottom_y = min(h, y + 5)
break
# Vertical projection for left/right margins
# --- Vertical projection for left/right margins ---
v_proj = np.sum(inv[top_y:bottom_y, :], axis=0).astype(float)
v_proj_norm = v_proj / ((bottom_y - top_y) * 255) if (bottom_y - top_y) > 0 else v_proj
v_mask = v_proj_norm > threshold
min_v_run = max(5, w // 100)
v_mask = _filter_narrow_runs(v_mask, min_v_run)
left_x = 0
for x in range(w):
if v_proj_norm[x] > 0.005:
if v_mask[x]:
left_x = max(0, x - 2)
break
right_x = w
for x in range(w - 1, 0, -1):
if v_proj_norm[x] > 0.005:
if v_mask[x]:
right_x = min(w, x + 2)
break
@@ -1993,12 +2021,58 @@ def _score_role(geom: ColumnGeometry) -> Dict[str, float]:
return {k: round(v, 3) for k, v in scores.items()}
def _build_margin_regions(
all_regions: List[PageRegion],
left_x: int,
right_x: int,
img_w: int,
top_y: int,
content_h: int,
) -> List[PageRegion]:
"""Create margin_left / margin_right PageRegions from content bounds.
Margins represent the space between the image edge and the first/last
content column. They are used downstream for faithful page
reconstruction but are skipped during OCR.
"""
margins: List[PageRegion] = []
# Minimum gap (px) to create a margin region
_min_gap = 5
if left_x > _min_gap:
margins.append(PageRegion(
type='margin_left', x=0, y=top_y,
width=left_x, height=content_h,
classification_confidence=1.0,
classification_method='content_bounds',
))
# Right margin: from end of last content column to image edge
non_margin = [r for r in all_regions
if r.type not in ('margin_left', 'margin_right', 'header', 'footer')]
if non_margin:
last_col_end = max(r.x + r.width for r in non_margin)
else:
last_col_end = right_x
if img_w - last_col_end > _min_gap:
margins.append(PageRegion(
type='margin_right', x=last_col_end, y=top_y,
width=img_w - last_col_end, height=content_h,
classification_confidence=1.0,
classification_method='content_bounds',
))
return margins
def classify_column_types(geometries: List[ColumnGeometry],
content_w: int,
top_y: int,
img_w: int,
img_h: int,
bottom_y: int) -> List[PageRegion]:
bottom_y: int,
left_x: int = 0,
right_x: int = 0) -> List[PageRegion]:
"""Classify column types using a 3-level fallback chain.
Level 1: Content-based (language + role scoring)
@@ -2012,21 +2086,28 @@ def classify_column_types(geometries: List[ColumnGeometry],
img_w: Full image width.
img_h: Full image height.
bottom_y: Bottom Y of content area.
left_x: Left content bound (from _find_content_bounds).
right_x: Right content bound (from _find_content_bounds).
Returns:
List of PageRegion with types, confidence, and method.
"""
content_h = bottom_y - top_y
def _with_margins(result: List[PageRegion]) -> List[PageRegion]:
"""Append margin_left / margin_right regions to *result*."""
margins = _build_margin_regions(result, left_x, right_x, img_w, top_y, content_h)
return result + margins
# Special case: single column → plain text page
if len(geometries) == 1:
geom = geometries[0]
return [PageRegion(
return _with_margins([PageRegion(
type='column_text', x=geom.x, y=geom.y,
width=geom.width, height=geom.height,
classification_confidence=0.9,
classification_method='content',
)]
)])
# --- Pre-filter: first/last columns with very few words → column_ignore ---
ignore_regions = []
@@ -2050,7 +2131,7 @@ def classify_column_types(geometries: List[ColumnGeometry],
# Handle edge case: all columns ignored or only 1 left
if len(geometries) == 0:
return ignore_regions
return _with_margins(ignore_regions)
if len(geometries) == 1:
geom = geometries[0]
ignore_regions.append(PageRegion(
@@ -2059,7 +2140,7 @@ def classify_column_types(geometries: List[ColumnGeometry],
classification_confidence=0.9,
classification_method='content',
))
return ignore_regions
return _with_margins(ignore_regions)
# --- Score all columns ---
lang_scores = [_score_language(g.words) for g in geometries]
@@ -2075,20 +2156,20 @@ def classify_column_types(geometries: List[ColumnGeometry],
if regions is not None:
logger.info("ClassifyColumns: Level 1 (content-based) succeeded")
_add_header_footer(regions, top_y, bottom_y, img_w, img_h)
return ignore_regions + regions
return _with_margins(ignore_regions + regions)
# --- Level 2: Position + language enhanced ---
regions = _classify_by_position_enhanced(geometries, lang_scores, content_w, content_h)
if regions is not None:
logger.info("ClassifyColumns: Level 2 (position+language) succeeded")
_add_header_footer(regions, top_y, bottom_y, img_w, img_h)
return ignore_regions + regions
return _with_margins(ignore_regions + regions)
# --- Level 3: Pure position fallback (old code, no regression) ---
logger.info("ClassifyColumns: Level 3 (position fallback)")
regions = _classify_by_position_fallback(geometries, content_w, content_h)
_add_header_footer(regions, top_y, bottom_y, img_w, img_h)
return ignore_regions + regions
return _with_margins(ignore_regions + regions)
def _classify_by_content(geometries: List[ColumnGeometry],
@@ -2490,7 +2571,8 @@ def analyze_layout_by_words(ocr_img: np.ndarray, dewarped_bgr: np.ndarray) -> Li
content_w = right_x - left_x
# Phase B: Content-based classification
regions = classify_column_types(geometries, content_w, top_y, w, h, bottom_y)
regions = classify_column_types(geometries, content_w, top_y, w, h, bottom_y,
left_x=left_x, right_x=right_x)
col_count = len([r for r in regions if r.type.startswith('column') or r.type == 'page_ref'])
methods = set(r.classification_method for r in regions if r.classification_method)
@@ -3602,7 +3684,7 @@ def build_cell_grid(
return [], []
# Use columns only — skip ignore, header, footer, page_ref
_skip_types = {'column_ignore', 'header', 'footer', 'page_ref'}
_skip_types = {'column_ignore', 'header', 'footer', 'page_ref', 'margin_left', 'margin_right'}
relevant_cols = [c for c in column_regions if c.type not in _skip_types]
if not relevant_cols:
logger.warning("build_cell_grid: no usable columns found")
@@ -3764,7 +3846,7 @@ def build_cell_grid_streaming(
if not content_rows:
return
_skip_types = {'column_ignore', 'header', 'footer', 'page_ref'}
_skip_types = {'column_ignore', 'header', 'footer', 'page_ref', 'margin_left', 'margin_right'}
relevant_cols = [c for c in column_regions if c.type not in _skip_types]
if not relevant_cols:
return
@@ -4249,8 +4331,9 @@ def run_multi_pass_ocr(ocr_img: np.ndarray,
"""
results: Dict[str, List[Dict]] = {}
_ocr_skip = {'header', 'footer', 'margin_left', 'margin_right'}
for region in regions:
if region.type == 'header' or region.type == 'footer':
if region.type in _ocr_skip:
continue # Skip non-content regions
if region.type == 'column_en':

View File

@@ -32,6 +32,8 @@ from cv_vocab_pipeline import (
create_ocr_image,
create_layout_image,
_find_content_bounds,
_filter_narrow_runs,
_build_margin_regions,
analyze_layout,
_group_words_into_lines,
match_lines_to_vocab,
@@ -843,6 +845,150 @@ class TestMergeContinuationRows:
assert len(result) == 2
# =============================================
# Test: Content-Bounds Scan-Artifact Filtering
# =============================================
class TestContentBoundsFiltering:
"""Test that _find_content_bounds filters narrow scan artifacts."""
def test_thin_vertical_line_ignored(self):
"""A 2px black line at the left edge should not pull left_x leftward."""
inv = np.zeros((400, 600), dtype=np.uint8)
# Main content block in the middle
inv[50:350, 100:550] = 255
# 2px thin vertical scan artifact at x=5..6
inv[50:350, 5:7] = 255
left, right, top, bottom = _find_content_bounds(inv)
# left_x must be near 100 (the real content), not near 5
assert left >= 90, f"left_x={left} should be >=90 (near real content, not artifact)"
def test_thick_content_preserved(self):
"""A 50px wide text block is real content and must not be filtered."""
inv = np.zeros((400, 600), dtype=np.uint8)
inv[50:350, 80:130] = 255 # 50px wide block
inv[50:350, 200:500] = 255 # wider block
left, right, top, bottom = _find_content_bounds(inv)
assert left <= 82, f"left_x={left} should be <=82 (50px block is real content)"
def test_no_artifacts_unchanged(self):
"""Normal image without artifacts: bounds should match content."""
inv = np.zeros((400, 600), dtype=np.uint8)
inv[100:300, 50:550] = 255
left, right, top, bottom = _find_content_bounds(inv)
assert left <= 52
assert right >= 548
assert top <= 105
assert bottom >= 295
def test_right_edge_artifact_ignored(self):
"""A thin vertical line at the right edge should not pull right_x rightward."""
inv = np.zeros((400, 600), dtype=np.uint8)
inv[50:350, 50:500] = 255 # real content
inv[50:350, 595:598] = 255 # 3px artifact at right edge
left, right, top, bottom = _find_content_bounds(inv)
assert right <= 510, f"right_x={right} should be <=510, ignoring right-edge artifact"
def test_horizontal_line_ignored(self):
"""A thin horizontal line at the top should not pull top_y upward."""
inv = np.zeros((400, 600), dtype=np.uint8)
inv[100:350, 50:550] = 255 # real content
inv[2:4, 50:550] = 255 # 2px horizontal artifact at top
left, right, top, bottom = _find_content_bounds(inv)
assert top >= 90, f"top_y={top} should be >=90 (ignoring thin top line)"
class TestFilterNarrowRuns:
"""Test the _filter_narrow_runs helper directly."""
def test_removes_short_run(self):
mask = np.array([False, True, True, False, True, True, True, True, True, False])
result = _filter_narrow_runs(mask, min_width=3)
# The 2-wide run at indices 1-2 should be removed
assert not result[1]
assert not result[2]
# The 5-wide run at indices 4-8 should remain
assert result[4]
assert result[8]
def test_keeps_wide_run(self):
mask = np.array([True] * 10)
result = _filter_narrow_runs(mask, min_width=5)
assert all(result)
def test_all_narrow(self):
mask = np.array([True, True, False, True, False])
result = _filter_narrow_runs(mask, min_width=3)
assert not any(result)
# =============================================
# Test: Margin Regions
# =============================================
class TestMarginRegions:
"""Test _build_margin_regions and margin integration."""
def test_margin_left_created(self):
"""When left_x > 5, a margin_left region should be created."""
existing = [
PageRegion(type='column_en', x=100, y=50, width=200, height=300),
PageRegion(type='column_de', x=320, y=50, width=200, height=300),
]
margins = _build_margin_regions(existing, left_x=100, right_x=520,
img_w=600, top_y=50, content_h=300)
left_margins = [m for m in margins if m.type == 'margin_left']
assert len(left_margins) == 1
ml = left_margins[0]
assert ml.x == 0
assert ml.width == 100
def test_margin_right_created(self):
"""When there's space after the last column, margin_right should be created."""
existing = [
PageRegion(type='column_en', x=50, y=50, width=200, height=300),
PageRegion(type='column_de', x=260, y=50, width=200, height=300),
]
# last_col_end = 260 + 200 = 460, img_w = 600 → gap = 140
margins = _build_margin_regions(existing, left_x=50, right_x=460,
img_w=600, top_y=50, content_h=300)
right_margins = [m for m in margins if m.type == 'margin_right']
assert len(right_margins) == 1
mr = right_margins[0]
assert mr.x == 460
assert mr.width == 140
def test_no_margin_when_flush(self):
"""When columns are flush with the image edges, no margins should appear."""
existing = [
PageRegion(type='column_en', x=0, y=0, width=300, height=400),
PageRegion(type='column_de', x=300, y=0, width=300, height=400),
]
margins = _build_margin_regions(existing, left_x=0, right_x=600,
img_w=600, top_y=0, content_h=400)
assert len(margins) == 0
def test_margins_in_skip_types(self):
"""Verify margin types are in the skip set used by build_cell_grid."""
skip = {'column_ignore', 'header', 'footer', 'page_ref', 'margin_left', 'margin_right'}
assert 'margin_left' in skip
assert 'margin_right' in skip
def test_margin_confidence_and_method(self):
"""Margin regions should have confidence 1.0 and method 'content_bounds'."""
existing = [PageRegion(type='column_en', x=80, y=20, width=400, height=500)]
margins = _build_margin_regions(existing, left_x=80, right_x=480,
img_w=600, top_y=20, content_h=500)
for m in margins:
assert m.classification_confidence == 1.0
assert m.classification_method == 'content_bounds'
# =============================================
# RUN TESTS
# =============================================