diff --git a/landmarks.py b/landmarks.py
index 8f6280b..893face 100644
--- a/landmarks.py
+++ b/landmarks.py
@@ -280,6 +280,7 @@ class Landmarker:
         distance = math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
         return distance
 
+
     def get_center_top_point(self, side_results):
         gray_image = cv2.cvtColor(
             self.side_image_keypoints,
@@ -290,42 +291,65 @@ class Landmarker:
             0 : int(self.side_image_resized.shape[0] / 2),
             :,
         ]
-        self.edges = cv2.Canny(roi, 50, 150)
+        edges = cv2.Canny(roi, 50, 150)
         contours, _ = cv2.findContours(
-            self.edges.copy(),
-            cv2.RETR_TREE,
+            edges,
+            cv2.RETR_EXTERNAL,
             cv2.CHAIN_APPROX_SIMPLE,
         )
-        max_contour = max(contours, key=cv2.contourArea)
-        rect = cv2.minAreaRect(max_contour)
-        box = cv2.boxPoints(rect)
-        box = sorted(
-            list(box),
-            key=lambda p: p[1],
-        )
-        top_point = min(
-            box[0],
-            box[1],
-            key=lambda p: p[0],
-        )
-
-        left_hip = side_results.pose_landmarks.landmark[LANDMARK_NAME_TO_INDEX["left_hip"]]
-        right_hip = side_results.pose_landmarks.landmark[LANDMARK_NAME_TO_INDEX["right_hip"]]
-        
-        center_x = (left_hip.x + right_hip.x) / 2
-        center_y = (left_hip.y + right_hip.y) / 2
-        
-        center_x, center_y = (
-            int(center_x * self.resized_width),
-            int(center_y * self.resized_height),
-        )
-        
-        self.pixel_distance = self.euclidean_distance(
-            top_point[0],
-            top_point[1],
-            center_x,
-            center_y,
-        )
+        xt, yt = None, None
+        topmost_point = None
+    
+        if contours:
+            largest_contour = max(
+                contours,
+                key=cv2.contourArea,
+            )
+            topmost_point = tuple(largest_contour[largest_contour[:, :, 1].argmin()][0])
+            xt, yt = topmost_point
+    
+            cv2.circle(
+                self.side_image_keypoints,
+                (xt, yt),
+                2,
+                (255, 255, 0),
+                -1,
+            )
+    
+        xc, yc = None, None
+        landmarks = side_results.pose_landmarks.landmark
+    
+        if side_results.pose_landmarks:
+            left_hip = landmarks[LANDMARK_NAME_TO_INDEX["left_hip"]]
+            right_hip = landmarks[LANDMARK_NAME_TO_INDEX["right_hip"]]
+            center_point = (
+                (left_hip.x + right_hip.x) / 2,
+                (left_hip.y + right_hip.y) / 2,
+            )
+            center_point = (
+                int(center_point[0] * self.side_image_resized.shape[1]),
+                int(center_point[1] * self.side_image_resized.shape[0]),
+            )
+            xc, yc = center_point
+            self.circle(
+                self.side_image_keypoints,
+                xc,
+                yc,
+            )
+    
+            self.pixel_distance = self.euclidean_distance(xc, yc, xt, yt)
+            logging.debug(
+                "top_center_pixel_distance: %s",
+                self.pixel_distance,
+            )
+            self.pixel_height = self.pixel_distance * 2
+            logging.debug(
+                "pixel height: %s ",
+                self.pixel_height,
+            )
+            self.distance = self.euclidean_distance(xc, yc, xt, yt) * self.pixel_to_metric_ratio()
+    
+        return self.distance
 
 if __name__ == "__main__":
     landmarker = Landmarker()