diff --git a/version.md b/version.md
index 9bf629d..f1616c5 100644
--- a/version.md
+++ b/version.md
@@ -21,4 +21,5 @@
 # 2.15.8 启动不加载预加载yolo
 # 2.15.9 20cm
 # 2.15.10 不保存图片
-# 2.15.11 优化内存
\ No newline at end of file
+# 2.15.11 优化内存
+# 2.15.12 优化算法
\ No newline at end of file
diff --git a/version.py b/version.py
index 46de01c..07953c8 100644
--- a/version.py
+++ b/version.py
@@ -4,6 +4,6 @@
 应用版本号
 每次 OTA 更新时，只需要更新这个文件中的版本号
 """
-VERSION = '2.15.11'
+VERSION = '2.15.12'
 
 
diff --git a/vision.py b/vision.py
index 556803f..cb3f7b8 100644
--- a/vision.py
+++ b/vision.py
@@ -570,11 +570,13 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
 
     # -- 3. 红色掩码：在循环外只算一次
     mask_red = cv2.bitwise_or(
-        cv2.inRange(hsv, np.array([0, 50, 40]),   np.array([10,  255, 255])),
-        cv2.inRange(hsv, np.array([170, 50, 40]), np.array([180, 255, 255])),
+        cv2.inRange(hsv, np.array([0, 30, 20]),   np.array([12,  255, 255])),
+        cv2.inRange(hsv, np.array([168, 30, 20]), np.array([180, 255, 255])),
     )
     kernel_red = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
     mask_red = cv2.morphologyEx(mask_red, cv2.MORPH_CLOSE, kernel_red)
+    # 再加一次膨胀，加厚环状区域避免碎片化
+    mask_red = cv2.dilate(mask_red, kernel_red, iterations=1)
     contours_red, _ = cv2.findContours(mask_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
     # 预先把红色轮廓筛选成 (center, radius) 列表，后续直接查表
     red_candidates = []
@@ -583,7 +585,7 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
         if ar <= 10:
             continue
         pr = cv2.arcLength(cnt_r, True)
-        if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.3:
+        if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.2:
             continue
         if len(cnt_r) >= 5:
             (xr, yr), (wr, hr), _ = cv2.fitEllipse(cnt_r)
@@ -625,7 +627,11 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
             ddx = yellow_center[0] - rc["center"][0]
             ddy = yellow_center[1] - rc["center"][1]
             dist_centers = math.hypot(ddx, ddy)
-            if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.7:
+            max_dist = yellow_radius * 2.0
+            min_r = min(rc["radius"], yellow_radius)
+            max_r = max(rc["radius"], yellow_radius)
+            size_ratio = min_r / max_r if max_r > 0 else 0
+            if dist_centers < max_dist and size_ratio > 0.5:
                 if logger:
                     logger.info(f"[target] -> 找到匹配的红圈: 黄心({yellow_center}), "
                                 f"红心({rc['center']}), 距离:{dist_centers:.1f}, "
@@ -638,8 +644,17 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
                 })
                 matched = True
                 break
-        if not matched and logger:
-            logger.debug("Debug -> 未找到匹配的红色圆圈，可能是误识别")
+        if not matched:
+            # 黄圈高置信度兜底：大且圆时跳过红圈验证
+            if area > 300 and circularity > 0.85:
+                valid_targets.append({
+                    "center": yellow_center,
+                    "radius": yellow_radius,
+                    "ellipse": yellow_ellipse,
+                    "area": area,
+                })
+            elif logger:
+                logger.debug("Debug -> 未找到匹配的红色圆圈，可能是误识别")
 
     logger.debug(f"[detect_circle_v3] step 4 fin {datetime.now()}")