diff --git a/src/common/vision/detectors/dual_norm.py b/src/common/vision/detectors/dual_norm.py
index c772ebe..9bd92af 100644
--- a/src/common/vision/detectors/dual_norm.py
+++ b/src/common/vision/detectors/dual_norm.py
@@ -5,6 +5,8 @@
 適応的閾値で局所ムラにも対応する二重防壁構成
 """
 
+import time
+
 import cv2
 import numpy as np
 
@@ -20,12 +22,56 @@
     apply_width_filter,
 )
 
+# 内訳計測用の累積値
+_profile_count: int = 0
+_profile_sums: dict[str, float] = {}
+_profile_start: float = 0.0
+_PROFILE_INTERVAL: float = 3.0
+
+
+def _profile_reset() -> None:
+    """計測値をリセットする"""
+    global _profile_count, _profile_sums, _profile_start
+    _profile_count = 0
+    _profile_sums = {}
+    _profile_start = time.time()
+
+
+def _profile_record(label: str, elapsed: float) -> None:
+    """計測値を記録する"""
+    _profile_sums[label] = (
+        _profile_sums.get(label, 0.0) + elapsed
+    )
+
+
+def _profile_print() -> None:
+    """計測結果を出力する"""
+    global _profile_count, _profile_start
+    if _profile_count == 0:
+        return
+    elapsed = time.time() - _profile_start
+    if elapsed < _PROFILE_INTERVAL:
+        return
+    parts = []
+    for label, total in _profile_sums.items():
+        avg = total / _profile_count * 1000.0
+        parts.append(f"{label}={avg:.1f}ms")
+    print(f"Pi: dual_norm内訳({_profile_count}f) "
+          + " ".join(parts))
+    _profile_reset()
+
 
 def detect_dual_norm(
     frame: np.ndarray, params: ImageParams,
 ) -> LineDetectResult:
     """案B: 二重正規化型"""
+    global _profile_count
+
+    if _profile_count == 0 and not _profile_sums:
+        _profile_reset()
+
     # 背景除算正規化
+    t0 = time.time()
     bg_k = params.bg_blur_ksize | 1
     bg = cv2.GaussianBlur(
         frame, (bg_k, bg_k), 0,
@@ -37,6 +83,8 @@
     normalized = np.clip(
         normalized, 0, 255,
     ).astype(np.uint8)
+    t1 = time.time()
+    _profile_record("背景除算", t1 - t0)
 
     # 適応的閾値（ガウシアン，BINARY_INV）
     block = max(params.adaptive_block | 1, 3)
@@ -54,6 +102,8 @@
             255, cv2.THRESH_BINARY_INV,
         )
         binary = cv2.bitwise_and(binary, global_mask)
+    t2 = time.time()
+    _profile_record("閾値処理", t2 - t1)
 
     # 段階クロージング or 等方クロージング
     if params.stage_min_area > 0:
@@ -79,11 +129,20 @@
             params.width_far,
             params.width_tolerance,
         )
+    t3 = time.time()
+    _profile_record("後処理", t3 - t2)
 
     # 行ごと中心抽出 + フィッティング
-    return fit_row_centers(
+    result = fit_row_centers(
         binary, params.min_line_width,
         median_ksize=params.median_ksize,
         neighbor_thresh=params.neighbor_thresh,
         residual_thresh=params.residual_thresh,
     )
+    t4 = time.time()
+    _profile_record("fitting", t4 - t3)
+
+    _profile_count += 1
+    _profile_print()
+
+    return result