Rabin-Karp algorithm for Pattern Searching in Matrix

Difficulty Level : Hard
Last Updated : 28 Jul, 2020

Given matrices txt[][] of dimensions m1 x m2 and pattern pat[][] of dimensions n1 x n2, the task is to check whether a pattern exists in the matrix or not and if yes then print the top mot indices od the pat[][] in txt[][]. It is assumed that m1, m2 ≥ n1, n2

Examples:

Input:
txt[][] = {{G, H, I, P}
           {J, K, L, Q}
           {R, G, H, I}  
           {S, J, K, L}
          }
pat[][] = {{G, H, I},
           {J, K, L}
          }
Output:
Pattern found at ( 0, 0 )
Pattern found at ( 2, 1 )
Explanation:


Input:
txt[][] = { {A, B, C},
            {D, E, F},
            {G, H, I}
          }
pat[][] = { {E, F},
            {H, I}
          }
Output:
Pattern found at (1, 1)

Approach: In order to find a pattern in a 2-D array using Rabin-Karp algorithm, consider an input matrix txt[m1][m2] and a pattern pat[n1][n2]. The idea is to find the hash of each columns of mat[][] and pat[][] and compare the hash values. For any column if hash values are equals than check for the corresponding rows values. Below are the steps:

Find the hash values of each column for the first N1 rows in both txt[][] and pat[][] matrix.
Apply Rabin-Karp Algorithm by finding hash values for the column hashes found in step 1.
If a match is found compare txt[][] and pat[][] matrices for the specific rows and columns.
Else slide down the column hashes by 1 row in the txt matrix using a rolling hash.
Repeat steps 2 to 4 for all the hash values and if we found any pat[][] match in txt[][] then print the indices of top most cell in the txt[][].

To find the hash value: In order to find the hash value of a substring of size N in a text using rolling hash follow below steps:

Remove the first character from the string: hash(txt[s:s+n-1])-(radix**(n-1)*txt[s])%prime_number
Add the next character to the string: hash(txt[s:s+n-1])*radix + txt[n]

Below is the implementation of the above approach:

Python3

# Python implementation for the  
# pattern matching in 2-D matrix 
  
# Function to find the hash-value  
# of the given columns of text 
def findHash(arr, col, row): 
    hashCol = [] 
    add = 0
    radix = 256
  
    # For each column 
    for i in range(0, col): 
  
        for j in reversed(range(0, row)): 
            add = add + (radix**(row-j-1) * 
                         ord(arr[j][i]))% 101
        hashCol.append(add % 101); 
        add = 0
    return hashCol 
  
# Function to check equality of the  
# two strings 
def checkEquality(txt, row, col, flag): 
    txt = [txt[i][col:patCol + col]  
           for i in range(row, patRow + row)] 
  
# If pattern found 
    if txt == pat: 
        flag = 1
        print("Pattern found at", \ 
              "(", row, ", ", col, ")") 
    return flag 
      
# Function to find the hash value of 
# of the next column using rolling-hash 
# of the Rabin-karp 
def colRollingHash(txtHash, nxtRow): 
  
    radix = 256
  
    # Find the hash of the matrix 
    for j in range(len(txtHash)): 
        txtHash[j] = (txtHash[j]*radix \ 
                      + ord(txt[nxtRow][j]))% 101
        txtHash[j] = txtHash[j] - (radix**(patRow) * 
                     ord(txt[nxtRow-patRow][j]))% 101 
        txtHash[j] = txtHash[j]% 101
    return txtHash 
      
  
# Function to match a pattern in  
# the given 2D Matrix 
def search(txt, pat): 
      
# List of the hashed value for 
    # the text and pattern columns 
    patHash = [] 
    txtHash = [] 
  
    # Hash value of the  
    # pat_hash and txt_hash 
    patVal = 0
    txtVal = 0 
  
    # Radix value for the input characters 
    radix = 256
      
    # Variable to determine if 
    # pattern was found or not 
    flag = 0
      
    # Function call to find the 
    # hash value of columns 
    txtHash = findHash(txt, txtCol, patRow)   
    patHash = findHash(pat, patCol, patRow) 
      
    # Calculate hash value for patHash 
    for i in range(len(patHash)): 
        patVal = patVal \ 
                 + (radix**(len(patHash)-i-1) * 
                 patHash[i]% 101) 
    patVal = patVal % 101
      
      
    # Applying Rabin-Karp to compare 
    # txtHash and patHash 
    for i in range(patRow-1, txtRow): 
        col = 0
        txtVal = 0
          
        # Find the hash value txtHash  
        for j in range(len(patHash)): 
            txtVal = txtVal\ 
                     + (radix**(len(patHash)-j-1) * 
                     txtHash[j])% 101
        txtVal = txtVal % 101
          
        if txtVal == patVal: 
            flag = checkEquality(\ 
                     txt, i + 1-patRow, col, flag) 
              
        else: 
  
            # Roll the txt window by one character  
            for k in range(len(patHash), len(txtHash)): 
  
                txtVal = txtVal \ 
                         * radix + (txtHash[k])% 101
                txtVal = txtVal \ 
                         - (radix**(len(patHash)) *
                         (txtHash[k-len(patHash)]))% 101
                txtVal = txtVal % 101
                col = col + 1
  
                # Check if txtVal and patVal are equal 
                if patVal == txtVal: 
                    flag = checkEquality(\ 
                           txt, i + 1-patRow, col, flag)    
                else: 
                    continue
                  
        # To make sure i does not exceed txtRow 
        if i + 1<txtRow: 
            txtHash = colRollingHash(txtHash, i + 1) 
              
    if flag == 0: 
        print("Pattern not found") 
      
  
# Driver Code 
if __name__ == "__main__": 
  
  # Given Text 
  txt = [['A', 'B', 'C'], \ 
         ['D', 'E', 'F'], \ 
         ['G', 'H', 'I']] 
  
  # Given Pattern 
  pat = [['E', 'F'], ['H', 'I']] 
  
  # Dimensions of the text 
  txtRow = 3
  txtCol = 3
  
  # Dimensions for the pattern 
  patRow = 2
  patCol = 2
  
  # Function Call 
  search(txt, pat) 

Output:

Pattern found at ( 1 ,  1 )

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