diff --git a/cv_analysis/layout_parsing.py b/cv_analysis/layout_parsing.py
index 6bb9d68..1a9718b 100644
--- a/cv_analysis/layout_parsing.py
+++ b/cv_analysis/layout_parsing.py
@@ -3,14 +3,11 @@ from typing import Iterable
 
 import cv2
 import numpy as np
-from funcy import lmap, compose, rcompose, first, lkeep
+from funcy import compose, rcompose, first, lkeep
 
-from cv_analysis.utils.connect_rects import connect_related_rects2
-from cv_analysis.utils.conversion import box_to_rectangle, rectangle_to_box
-from cv_analysis.utils.postprocessing import (
-    remove_included,
-    has_no_parent,
-)
+from cv_analysis.utils.connect_rects import connect_related_rectangles
+from cv_analysis.utils.conversion import box_to_rectangle
+from cv_analysis.utils.postprocessing import remove_included, has_no_parent
 from cv_analysis.utils.rectangle import Rectangle
 
 
@@ -18,9 +15,7 @@ def parse_layout(image: np.array):
 
     rectangles = find_segments(image)
     rectangles = remove_included(rectangles)
-    boxes = lmap(rectangle_to_box, rectangles)
-    boxes = connect_related_rects2(boxes)
-    rectangles = lmap(box_to_rectangle, boxes)
+    rectangles = connect_related_rectangles(rectangles)
     rectangles = remove_included(rectangles)
 
     return rectangles
@@ -60,13 +55,18 @@ def find_contours(image):
 
 
 def is_likely_segment(rect, min_area=100):
+    # FIXME: Parameterize via factory
     return cv2.contourArea(rect, False) > min_area
 
 
 def dilate_page_components(image):
+    # FIXME: Parameterize via factory
     image = cv2.GaussianBlur(image, (7, 7), 0)
+    # FIXME: Parameterize via factory
     thresh = cv2.threshold(image, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
+    # FIXME: Parameterize via factory
     kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
+    # FIXME: Parameterize via factory
     return cv2.dilate(thresh, kernel, iterations=4)
 
 
@@ -87,6 +87,7 @@ def normalize_to_gray_scale(image):
 
 
 def threshold_image(image):
+    # FIXME: Parameterize via factory
     _, image = cv2.threshold(image, 254, 255, cv2.THRESH_BINARY)
     return image
 
diff --git a/cv_analysis/utils/connect_rects.py b/cv_analysis/utils/connect_rects.py
index 3c67777..abc1fd2 100644
--- a/cv_analysis/utils/connect_rects.py
+++ b/cv_analysis/utils/connect_rects.py
@@ -1,7 +1,9 @@
 from itertools import combinations, starmap, product
 from typing import Iterable
 
-from cv_analysis.utils.conversion import rectangle_to_box
+from funcy import lfilter, lmap
+
+from cv_analysis.utils.conversion import rectangle_to_box, box_to_rectangle
 from cv_analysis.utils.rectangle import Rectangle
 
 
@@ -38,9 +40,9 @@ def is_on_same_line(rect_pair):
     )
 
 
-def has_correct_position1(rect_pair):
-    x1, y1, w1, h1 = rect_pair[0]
-    x2, y2, w2, h2 = rect_pair[1]
+def has_correct_position(alpha: Rectangle, beta: Rectangle):
+    x1, y1, w1, h1 = alpha
+    x2, y2, w2, h2 = beta
     return any(
         [
             any(
@@ -59,7 +61,7 @@ def has_correct_position1(rect_pair):
 
 
 def is_related(rect_pair):
-    return (is_near_enough(rect_pair) and has_correct_position1(rect_pair)) or is_overlapping(rect_pair)
+    return (is_near_enough(rect_pair) and has_correct_position(*rect_pair)) or is_overlapping(rect_pair)
 
 
 def fuse_rects(rect1, rect2):
@@ -76,61 +78,41 @@ def fuse_rects(rect1, rect2):
     return tuple(topleft + w + h)
 
 
-def rects_not_the_same(r):
+def rectangles_differ(r):
     return r[0] != r[1]
 
 
 def find_related_rects(rects):
-    rect_pairs = list(filter(is_related, combinations(rects, 2)))
-    rect_pairs = list(filter(rects_not_the_same, rect_pairs))
+    rect_pairs = lfilter(is_related, combinations(rects, 2))
+    rect_pairs = lfilter(rectangles_differ, rect_pairs)
     if not rect_pairs:
         return [], rects
-    rel_rects = list(set([rect for pair in rect_pairs for rect in pair]))
+    rel_rects = set([rect for pair in rect_pairs for rect in pair])
     unrel_rects = [rect for rect in rects if rect not in rel_rects]
     return rect_pairs, unrel_rects
 
 
-def connect_related_rects(rects):
-    rects_to_connect, rects_new = find_related_rects(rects)
+def connect_related_rectangles(rectangles: Iterable[Rectangle]):
+    boxes = lmap(rectangle_to_box, rectangles)
 
-    while len(rects_to_connect) > 0:
-        rects_fused = list(starmap(fuse_rects, rects_to_connect))
-        rects_fused = list(dict.fromkeys(rects_fused))
-
-        if len(rects_fused) == 1:
-            rects_new += rects_fused
-            rects_fused = []
-
-        rects_to_connect, connected_rects = find_related_rects(rects_fused)
-        rects_new += connected_rects
-
-        if len(rects_to_connect) > 1 and len(set(rects_to_connect)) == 1:
-            rects_new.append(rects_fused[0])
-            rects_to_connect = []
-
-    return rects_new
-
-
-def connect_related_rects2(rects: Iterable[tuple]):
-    rects = list(rects)
     current_idx = 0
 
     while True:
-        if current_idx + 1 >= len(rects) or len(rects) <= 1:
+        if current_idx + 1 >= len(boxes) or len(boxes) <= 1:
             break
         merge_happened = False
-        current_rect = rects.pop(current_idx)
+        current_rect = boxes.pop(current_idx)
 
-        for idx, maybe_related_rect in enumerate(rects):
+        for idx, maybe_related_rect in enumerate(boxes):
             if is_related((current_rect, maybe_related_rect)):
                 current_rect = fuse_rects(current_rect, maybe_related_rect)
-                rects.pop(idx)
+                boxes.pop(idx)
                 merge_happened = True
                 break
-        rects.insert(0, current_rect)
+        boxes.insert(0, current_rect)
         if not merge_happened:
             current_idx += 1
         elif merge_happened:
             current_idx = 0
 
-    return rects
+    return lmap(box_to_rectangle, boxes)