From 17715a795e39e7f1ce2323ed7e15cd6e3400ed0d Mon Sep 17 00:00:00 2001 From: The Coding Aviator <34807532+thecodingaviator@users.noreply.github.com> Date: Mon, 18 Mar 2019 13:49:02 +0530 Subject: [PATCH] fix(formatting): Zhang-Suen | Rosetta Code (#35472) * fix(formatting): Move challenge instructions to instruction section * Fix table and list * fix(curriculum): Zhangsuen * fix(curriculum): add bold tags * Fix typo in instructions --- .../zhang-suen-thinning-algorithm.english.md | 57 ++++++++++--------- 1 file changed, 30 insertions(+), 27 deletions(-) diff --git a/curriculum/challenges/english/08-coding-interview-prep/rosetta-code/zhang-suen-thinning-algorithm.english.md b/curriculum/challenges/english/08-coding-interview-prep/rosetta-code/zhang-suen-thinning-algorithm.english.md index 66bc223c2f..4645cefec6 100644 --- a/curriculum/challenges/english/08-coding-interview-prep/rosetta-code/zhang-suen-thinning-algorithm.english.md +++ b/curriculum/challenges/english/08-coding-interview-prep/rosetta-code/zhang-suen-thinning-algorithm.english.md @@ -25,7 +25,7 @@ For example, with an input image of: ######## ####### ###### ################## ###### ######## ####### ###### ################ ###### ######## ####### ###### ############# ###### - + It produces the thinned output: 
 
@@ -44,49 +44,52 @@ It produces the thinned output:
      #                             ############
                        ###                          ###
 
-
+ +

Algorithm

Assume black pixels are one and white pixels zero, and that the input image is a rectangular N by M array of ones and zeroes. The algorithm operates on all black pixels P1 that can have eight neighbours. The neighbours are, in order, arranged as: - - - - + +
P9P2P3
P8P1P4
P7P6P5
+ + +
P9P2P3
P8P1P4
P7P6P5
+ Obviously the boundary pixels of the image cannot have the full eight neighbours. - - Define $A(P1)$ = the number of transitions from white to black, (0 -> 1) in the sequence P2,P3,P4,P5,P6,P7,P8,P9,P2. (Note the extra P2 at the end - it is circular). - - - Define $B(P1)$ = the number of black pixel neighbours of P1. ( = sum(P2 .. P9) ) +

Step 1:

All pixels are tested and pixels satisfying all the following conditions (simultaneously) are just noted at this stage. - (0) The pixel is black and has eight neighbours - (1) $2 <= B(P1) <= 6$ - (2) $A(P1) = 1$ - (3) At least one of P2 and P4 and P6 is white - (4) At least one of P4 and P6 and P8 is white +
    +
  1. The pixel is black and has eight neighbours
    2. +
  2. $2 <= B(P1) <= 6$
    3. +
  3. $A(P1) = 1$
    4. +
  4. At least one of P2, P4 and P6 is white
    5. +
  5. At least one of P4, P6 and P8 is white
    6. +
After iterating over the image and collecting all the pixels satisfying all step 1 conditions, all these condition satisfying pixels are set to white. +

Step 2:

All pixels are again tested and pixels satisfying all the following conditions are just noted at this stage. - (0) The pixel is black and has eight neighbours - (1) $2 <= B(P1) <= 6$ - (2) $A(P1) = 1$ - (3) At least one of P2 and P4 and '''P8''' is white - (4) At least one of '''P2''' and P6 and P8 is white +
    +
  1. The pixel is black and has eight neighbours
    2. +
  2. $2 <= B(P1) <= 6$
    3. +
  3. $A(P1) = 1$
    4. +
  4. At least one of P2, P4 and P8 is white
    5. +
  5. At least one of P2, P6 and P8 is white
    6. +
After iterating over the image and collecting all the pixels satisfying all step 2 conditions, all these condition satisfying pixels are again set to white. -Iteration: +

Iteration:

If any pixels were set in this round of either step 1 or step 2 then all steps are repeated until no image pixels are so changed. -

-Task: -Write a routine to perform Zhang-Suen thinning on an image matrix of ones and zeroes. -

## Instructions
- +Write a routine to perform Zhang-Suen thinning on the provided image matrix.
## Tests