from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import maximum_bipartite_matching

N, M = map(int, input().split())
S = [input() for _ in range(N)]


def idx2int(n, m):
    return (n * M + m) // 2


white, black = [], []
for x in range(N):
    for y in range(x % 2, M, 2):
        if S[x][y] == 'w':
            for dx, dy in ((1, 0), (0, 1), (-1, 0), (0, -1)):
                if 0 <= x + dx < N and 0 <= y + dy < M and S[x + dx][y + dy] == 'b':
                    white.append(idx2int(x, y))
                    black.append(idx2int(x + dx, y + dy))
w_count = sum(s.count('w') for s in S)
b_count = sum(s.count('b') for s in S)

matr = csr_matrix(([1] * len(white), (white, black)), shape=(N * M // 2, N * M // 2))
match = sum(maximum_bipartite_matching(matr, perm_type='column') != -1)

w_count -= match
b_count -= match
major, minor = max(w_count, b_count), min(w_count, b_count)
print(match * 100 + minor * 10 + major - minor)