---

def scan_frame(cell_board, color_database, templates_edges, ALL_PIECES, empty_threshold=12):
    board = cv2.resize(cell_board, (400, 400))
    board_matrix = []
    
    for row in range(8):
        row_pieces = []
        for col in range(8):
            cell = board[row * 50:(row + 1) * 50, col * 50:(col + 1) * 50]
            gray_cell = cv2.cvtColor(cell, cv2.COLOR_BGR2GRAY)
            
            # 1. Повышаем чёткость Canny (пороги 50, 150 лучше выделяют зубцы верхушек)
            cell_edge = cv2.Canny(gray_cell[7:43, 7:43], 50, 150)

            # Проверка на пустую клетку
            if np.count_nonzero(cell_edge) < empty_threshold:
                row_pieces.append('.')
                continue

            # 2. Определение цвета (белая / черная)
            cell_color_vec = np.array(extract_dominant_piece_color(cell))
            brightness = np.mean(cell_color_vec)
            
            is_white_piece = brightness > 110
            candidate_pieces = [p for p in ALL_PIECES if p.isupper() == is_white_piece]

            best_match, max_score = '.', -999.0

            for piece_symbol in candidate_pieces:
                if piece_symbol not in templates_edges or piece_symbol not in color_database:
                    continue
                
                # Сравнение формы Canny
                res = cv2.matchTemplate(cell_edge, templates_edges[piece_symbol], cv2.TM_CCOEFF_NORMED)
                _, shape_score, _, _ = cv2.minMaxLoc(res)
                
                # Штраф за цвет
                tpl_color = np.array(color_database[piece_symbol])
                color_dist = np.linalg.norm(cell_color_vec - tpl_color)
                
                score = shape_score - (color_dist / 150.0)
                
                # ДОПОЛНИТЕЛЬНЫЙ ВЕС ДЛЯ ВЕРХНЕЙ ЧАСТИ (Верхушки ладьи, ферзя и слона)
                # Сравниваем отдельно самые верхние 12 пикселей
                top_cell = cell_edge[:12, :]
                top_tpl = templates_edges[piece_symbol][:12, :]
                top_res = cv2.matchTemplate(top_cell, top_tpl, cv2.TM_CCOEFF_NORMED)
                _, top_score, _, _ = cv2.minMaxLoc(top_res)
                
                # Итоговый балл складывает общую форму + акцент на верхушке
                final_score = score + (top_score * 0.3)
                
                if final_score > max_score:
                    max_score = final_score
                    best_match = piece_symbol
                    
            row_pieces.append(best_match)
        board_matrix.append(row_pieces)

    # Формирование FEN
    fen_rows = []
    for r in board_matrix:
        empty, row_str = 0, ""
        for p in r:
            if p == '.': empty += 1
            else:
                if empty > 0: row_str += str(empty); empty = 0
                row_str += p
        if empty > 0: row_str += str(empty)
        fen_rows.append(row_str)
        
    return board_matrix, "/".join(fen_rows) + " w - - 0 1"