diff --git a/modules/python/src2/typing_stubs_generation/api_refinement.py b/modules/python/src2/typing_stubs_generation/api_refinement.py
index 3019e67e96..f92c5c8ce1 100644
--- a/modules/python/src2/typing_stubs_generation/api_refinement.py
+++ b/modules/python/src2/typing_stubs_generation/api_refinement.py
@@ -8,7 +8,7 @@ from .nodes import (NamespaceNode, FunctionNode, OptionalTypeNode, TypeNode,
                     ClassProperty, PrimitiveTypeNode, ASTNodeTypeNode,
                     AggregatedTypeNode, CallableTypeNode, AnyTypeNode,
                     TupleTypeNode, UnionTypeNode, ProtocolClassNode,
-                    DictTypeNode, ClassTypeNode)
+                    DictTypeNode, ClassTypeNode, AliasRefTypeNode)
 from .ast_utils import (find_function_node, SymbolName,
                         for_each_function_overload)
 from .types_conversion import create_type_node
@@ -376,6 +376,62 @@ def _find_argument_index(arguments: Sequence[FunctionNode.Arg],
     return None
 
 
+def make_matlike_or_scalar_arg(*arg_names: str) -> Callable[[NamespaceNode, SymbolName], None]:
+    """Make arguments accept both MatLike and Scalar types.
+
+    This is used for functions like inRange where the C++ InputArray parameter
+    can accept both Mat objects and Scalar values (tuples, floats, etc.).
+
+    Example: cv2.inRange(img, (0, 0, 0), (255, 255, 255)) should be valid.
+    """
+    def _make_matlike_or_scalar_arg(root_node: NamespaceNode,
+                                     function_symbol_name: SymbolName) -> None:
+        from .predefined_types import PREDEFINED_TYPES
+
+        function = find_function_node(root_node, function_symbol_name)
+        for arg_name in arg_names:
+            found_overload_with_arg = False
+
+            for overload in function.overloads:
+                arg_idx = _find_argument_index(overload.arguments, arg_name)
+
+                # skip overloads without this argument
+                if arg_idx is None:
+                    continue
+
+                current_type = overload.arguments[arg_idx].type_node
+
+                # Check if it's already a union or if it already includes Scalar
+                if isinstance(current_type, UnionTypeNode):
+                    # Check if Scalar is already in the union
+                    has_scalar = any(
+                        isinstance(item, AliasRefTypeNode) and item.typename == "Scalar"
+                        for item in current_type.items
+                    )
+                    if has_scalar:
+                        continue
+                    # Add Scalar to existing union
+                    scalar_ref = AliasRefTypeNode("Scalar")
+                    current_type.items = current_type.items + (scalar_ref,)
+                else:
+                    # Create a union of current type and Scalar
+                    scalar_ref = AliasRefTypeNode("Scalar")
+                    overload.arguments[arg_idx].type_node = UnionTypeNode(
+                        f"{arg_name}_type",
+                        (cast(TypeNode, current_type), scalar_ref)
+                    )
+
+                found_overload_with_arg = True
+
+            if not found_overload_with_arg:
+                raise RuntimeError(
+                    f"Failed to find argument with name: '{arg_name}'"
+                    f" in '{function_symbol_name.name}' overloads"
+                )
+
+    return _make_matlike_or_scalar_arg
+
+
 NODES_TO_REFINE = {
     SymbolName(("cv", ), (), "resize"): make_optional_arg("dsize"),
     SymbolName(("cv", ), (), "calcHist"): make_optional_arg("mask"),
@@ -401,6 +457,8 @@ NODES_TO_REFINE = {
     SymbolName(("cv", "fisheye"), (), "initUndistortRectifyMap"): make_optional_arg("D"),
     SymbolName(("cv", ), (), "imread"): make_optional_none_return,
     SymbolName(("cv", ), (), "imdecode"): make_optional_none_return,
+    # Fix for issue #28534: inRange should accept Scalar for lowerb and upperb
+    SymbolName(("cv", ), (), "inRange"): make_matlike_or_scalar_arg("lowerb", "upperb"),
 }
 
 ERROR_CLASS_PROPERTIES = (