diff --git a/vidocp/table_parsing.py b/vidocp/table_parsing.py
index 2301ac1..dd65cd2 100644
--- a/vidocp/table_parsing.py
+++ b/vidocp/table_parsing.py
@@ -9,6 +9,7 @@ from pdf2image import pdf2image
 from vidocp.utils.display import show_mpl
 from vidocp.utils.draw import draw_rectangles
 from vidocp.utils.post_processing import xywh_to_vecs, xywh_to_vec_rect, adjacent1d, remove_isolated
+from vidocp.layout_parsing import parse_layout
 
 
 def add_external_contours(image, img):
@@ -23,50 +24,8 @@ def add_external_contours(image, img):
     return image
 
 
-def process_lines(img_line_component):
-    def draw_lines(detected_lines, img_bin):
-        for line in detected_lines:
-            for x1, y1, x2, y2 in line:
-                cv2.line(img_bin, (x1, y1), (x2, y2), (255, 255, 255), 6)
-                return img_bin
-
-    lines = cv2.HoughLines(img_line_component, 1, np.pi / 180, 500)
-    draw_lines(lines, lines)
-
-    return img_line_component
-
-# def isolate_vertical_and_horizontal_components(img_bin):
-#     line_min_width = 50
-#     kernel_h = np.ones((1, line_min_width), np.uint8)
-#     kernel_v = np.ones((line_min_width, 1), np.uint8)
-#
-#     img_bin_h = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_h)
-#     img_bin_v = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_v)
-#     show_mpl(img_bin_h | img_bin_v)
-#
-#     img_bin_h = apply_motion_blur(img_bin_h, 140, 0)
-#     img_bin_v = apply_motion_blur(img_bin_v, 140, 90)
-#     show_mpl(img_bin_h | img_bin_v)
-#
-#     th1, img_bin_h = cv2.threshold(img_bin_h, 95, 255, cv2.THRESH_BINARY)
-#     th1, img_bin_v = cv2.threshold(img_bin_v, 95, 255, cv2.THRESH_BINARY)
-#     show_mpl(img_bin_h | img_bin_v)
-#
-#     kernel_h = np.ones((1, 8), np.uint8)
-#     kernel_v = np.ones((8, 1), np.uint8)
-#     img_bin_h = cv2.dilate(img_bin_h, kernel_h, iterations=4)
-#     img_bin_v = cv2.dilate(img_bin_v, kernel_v, iterations=4)
-#
-#     img_bin_final = img_bin_h | img_bin_v
-#     show_mpl(img_bin_final)
-#     # th 130
-#     #th1, img_bin_final = cv2.threshold(img_bin_final, 90, 255, cv2.THRESH_BINARY)
-#     #show_mpl(img_bin_final)
-#     return img_bin_final
-
-
-def isolate_vertical_and_horizontal_components(img_bin):
-    line_min_width = 30
+def isolate_vertical_and_horizontal_components(img_bin, bounding_rects):
+    line_min_width = 47
     kernel_h = np.ones((1, line_min_width), np.uint8)
     kernel_v = np.ones((line_min_width, 1), np.uint8)
 
@@ -74,51 +33,32 @@ def isolate_vertical_and_horizontal_components(img_bin):
     img_bin_v = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_v)
     show_mpl(img_bin_h | img_bin_v)
 
-    img_bin_h = apply_motion_blur(img_bin_h, 150, 0)
-    img_bin_v = apply_motion_blur(img_bin_v, 150, 90)
+    kernel_h = np.ones((1, 30), np.uint8)
+    kernel_v = np.ones((30, 1), np.uint8)
+    img_bin_h = cv2.dilate(img_bin_h, kernel_h, iterations=2)
+    img_bin_v = cv2.dilate(img_bin_v, kernel_v, iterations=2)
     show_mpl(img_bin_h | img_bin_v)
 
-    th1, img_bin_h = cv2.threshold(img_bin_h, 70, 255, cv2.THRESH_BINARY)
-    th1, img_bin_v = cv2.threshold(img_bin_v, 70, 255, cv2.THRESH_BINARY)
-    show_mpl(img_bin_h | img_bin_v)
-
-    kernel_h = np.ones((1, 10), np.uint8)
-    kernel_v = np.ones((10, 1), np.uint8)
-    img_bin_h = cv2.erode(img_bin_h, kernel_h, iterations=1)
-    img_bin_v = cv2.erode(img_bin_v, kernel_v, iterations=1)
+    img_bin_h = apply_motion_blur(img_bin_h, 100, 0)
+    img_bin_v = apply_motion_blur(img_bin_v, 100, 90)
 
     img_bin_final = img_bin_h | img_bin_v
     show_mpl(img_bin_final)
-    # th 130
-    # th1, img_bin_final = cv2.threshold(img_bin_final, 150, 255, cv2.THRESH_BINARY)
-    # show_mpl(img_bin_final)
+
+    th1, img_bin_final = cv2.threshold(img_bin_final, 110, 255, cv2.THRESH_BINARY)
+    img_bin_final = cv2.dilate(img_bin_final, np.ones((1, 1), np.uint8), iterations=1)
+    show_mpl(img_bin_final)
+    img_bin_final = disconnect_non_existing_cells(img_bin_final, bounding_rects)
+    show_mpl(img_bin_final)
+
     return img_bin_final
 
-# def isolate_vertical_and_horizontal_components(img_bin):
-#     line_min_width = 30
-#     kernel_h = np.ones((1, line_min_width), np.uint8)
-#     kernel_v = np.ones((line_min_width, 1), np.uint8)
-#
-#     img_bin_h = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_h)
-#     img_bin_v = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_v)
-#     show_mpl(img_bin_h | img_bin_v)
-#
-#     kernel_h = np.ones((1, 30), np.uint8)
-#     kernel_v = np.ones((30, 1), np.uint8)
-#     img_bin_h = cv2.dilate(img_bin_h, kernel_h, iterations=1)
-#     img_bin_v = cv2.dilate(img_bin_v, kernel_v, iterations=1)
-#     show_mpl(img_bin_h | img_bin_v)
-#
-#     img_bin_h = apply_motion_blur(img_bin_h, 100, 0)
-#     img_bin_v = apply_motion_blur(img_bin_v, 100, 90)
-#
-#     img_bin_final = img_bin_h | img_bin_v
-#     show_mpl(img_bin_final)
-#     # th 130
-#     th1, img_bin_final = cv2.threshold(img_bin_final, 125, 255, cv2.THRESH_BINARY)
-#     show_mpl(img_bin_final)
-#
-#     return img_bin_final
+
+def disconnect_non_existing_cells(img_bin, bounding_rects):
+    for rect in bounding_rects:
+        x, y, w, h = rect
+        img_bin = cv2.rectangle(img_bin, (x, y), (x + w, y + h), (0, 0, 0), 5)
+    return img_bin
 
 
 # FIXME: does not work yet
@@ -163,18 +103,28 @@ def apply_motion_blur(image, size, angle):
     return cv2.filter2D(image, -1, k)
 
 
+def find_table_layout_boxes(image: np.array):
+    layout_boxes = parse_layout(image)
+    table_boxes = []
+    for box in layout_boxes:
+        (x, y, w, h) = box
+        if w * h >= 300000:
+            table_boxes.append(box)
+    return table_boxes
+
+
 def parse_table(image: np.array):
     def is_large_enough(stat):
         x1, y1, w, h, area = stat
-        return area > 500 and w > 35 and h > 15
+        return area > 2000 and w > 35 and h > 25
 
     gray_scale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    # blur_gray_scale = cv2.GaussianBlur(gray_scale, (5, 5), 1, borderType=cv2.BORDER_REPLICATE)
     th1, img_bin = cv2.threshold(gray_scale, 195, 255, cv2.THRESH_BINARY)
     img_bin = ~img_bin
     show_mpl(img_bin)
 
-    img_bin = isolate_vertical_and_horizontal_components(img_bin)
+    table_layout_boxes = find_table_layout_boxes(image)
+    img_bin = isolate_vertical_and_horizontal_components(img_bin, table_layout_boxes)
     img_bin_final = add_external_contours(img_bin, img_bin)
 
     _, _, stats, _ = cv2.connectedComponentsWithStats(~img_bin_final, connectivity=8, ltype=cv2.CV_32S)
diff --git a/vidocp/utils/post_processing.py b/vidocp/utils/post_processing.py
index 6cc9452..02018c3 100644
--- a/vidocp/utils/post_processing.py
+++ b/vidocp/utils/post_processing.py
@@ -30,7 +30,7 @@ def remove_included(rectangles):
     return rectangles
 
 #tolerance was set too low (1) most lines are 2px wide
-def adjacent1d(n, m, tolerance=2):
+def adjacent1d(n, m, tolerance=4):
     return abs(n - m) <= tolerance