Flood Fill

Flood Fill is a Easy Data Structures and Algorithms interview problem you can solve, run and submit on Thita.ai. It belongs to the Graph Traversal Patterns (DFS & BFS) pattern, in the Graph DFS - Connected Components / Island Counting subpattern.

Problem statement

You are given an image represented by an m x n grid of integers image, where image[i][j] represents the pixel value of the image. You are also given three integers sr, sc, and color. Your task is to perform a flood fill on the image starting from the pixel image[sr][sc].

To perform a flood fill:

- Begin with the starting pixel and change its color to color.

- Perform the same process for each pixel that is directly adjacent (pixels that share a side with the original pixel, either horizontally or vertically) and shares the same color as the starting pixel.

- Keep repeating this process by checking neighboring pixels of the updated pixels and modifying their color if it matches the original color of the starting pixel.

- The process stops when there are no more adjacent pixels of the original color to update.

Return the modified image after performing the flood fill.

Example 1:

Input: image = [[1,1,1],[1,1,0],[1,0,1]], sr = 1, sc = 1, color = 2

Output: [[2,2,2],[2,2,0],[2,0,1]]

Explanation:

From the center of the image with position (sr, sc) = (1, 1) (i.e., the red pixel), all pixels connected by a path of the same color as the starting pixel (i.e., the blue pixels) are colored with the new color.

Note the bottom corner is not colored 2, because it is not horizontally or vertically connected to the starting pixel.

Example 2:

Input: image = [[0,0,0],[0,0,0]], sr = 0, sc = 0, color = 0

Output: [[0,0,0],[0,0,0]]

Explanation:

The starting pixel is already colored with 0, which is the same as the target color. Therefore, no changes are made to the image.

Constraints:

- m == image.length

- n == image[i].length

- 1 <= m, n <= 50

- 0 <= image[i][j], color < 216

- 0 <= sr < m

Topics and companies

Topics: Array, Depth-First Search, Breadth-First Search, Matrix.

Reported in interviews at Amazon, Apple, Bloomberg, Facebook, Google, Microsoft, Palantir Technologies, Qualtrics, Snapchat, Uber.

How to practise Flood Fill on Thita.ai

Starter code is provided in C, C#, C++, Go, Java, JavaScript and Python. Your solution runs against 5 test cases for this problem, with the AI coach available for a hint when you are stuck rather than a finished answer. The reference solution runs in O(m * n) where m and n are the dimensions of the image. In the worst case, every pixel is visited once. time and O(m * n) in the worst case due to the recursion stack (if the entire image is filled). space.

Open Flood Fill in the code editor, or read the Flood Fill editorial for a worked solution with its approach and complexity analysis.

Where Flood Fill sits in the DSA pattern sheet

Problems related to Flood Fill

Other problems that use the same Graph DFS - Connected Components / Island Counting and Graph Traversal Patterns (DFS & BFS) techniques:

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