000000
011110
010100
011100
010000
000000

In this case, when i and j are 1, your algorithm will set s = 3. The if 
statement will fail, and it will never notice that it could have formed a 
square with s=2.

Don

On Sunday, March 30, 2014 9:49:21 AM UTC-4, atul007 wrote:
>
> @don :  According to question we want to find  "the maximum subsquare".
> can you give me test case for which this wont work?
>
>
>
> On Fri, Mar 28, 2014 at 9:41 PM, Don <[email protected] <javascript:>>wrote:
>
>> No, that is not the same.
>> It won't find a square smaller than s.
>> Don
>>
>>
>> On Thursday, March 27, 2014 2:56:29 AM UTC-4, atul007 wrote:
>>
>>> @Don : your algo time complexity is O(n^2) 
>>>
>>> It can be reduced to this :- 
>>>
>>> // Now look for largest square with top left corner at (i,j) 
>>>   for(i = 0; i < n; ++i) 
>>>       for(j = 0; j < n; ++j) 
>>>       { 
>>>             s = Min(countRight[i][j], countDown[i][j]); 
>>>             if (countRight[i][j] && countDown[i][j] && 
>>> (countRight[i+s][j] >= s) && (countDown[i][j+s] >= s) && s>max) 
>>>             { 
>>>                bestI = i; bestJ = j; max = s; 
>>>             } 
>>>       } 
>>>
>>> On 1/25/13, Don <[email protected]> wrote: 
>>> > The worst case I know of is when the matrix is solid black except for 
>>> > the lower right quadrant. In this case, it does break down into O(n^3) 
>>> > runtime. It took about 8 times as long to run n=4000 as it took for 
>>> > n=2000. 
>>> > Don 
>>> > 
>>> > On Jan 24, 10:29 am, Don <[email protected]> wrote: 
>>> >> I'm not sure I understand your case. However, I stated that there are 
>>> >> cases where it is worse than O(N^2). The runtime is highly dependent 
>>> >> on the contents of the matrix. In many cases it takes fewer than N^2 
>>> >> iterations. Occasionally it takes more. On average it seems to be 
>>> >> roughly O(N^2), but again that depends a lot on what is in the 
>>> matrix. 
>>> >> I got that result by trying different ways of filling the matrix. I 
>>> >> tried things like randomly setting each pixel with various 
>>> >> probabilities, placing random horizontal and vertical segments, 
>>> >> placing random squares, or placing random filled squares. I did all 
>>> of 
>>> >> those both in black on white and white on black. In all of those 
>>> >> cases, going from n=1000 to n=2000 resulted in a runtime increase of 
>>> >> less than a factor of 4. 
>>> >> 
>>> >> Don 
>>> >> 
>>> >> On Jan 23, 10:33 pm, bharat b <[email protected]> wrote: 
>>> >> 
>>> >> 
>>> >> 
>>> >> 
>>> >> 
>>> >> 
>>> >> 
>>> >> > @Don: the solution is very nice.. But, how can u prove that it is 
>>> >> > O(n^2).. 
>>> >> > for me it seems to be O(n^3) .. 
>>> >> 
>>> >> > Ex: nxn matrix .. all 1s from (n/2,0) to (n/2,n/2). 
>>> >> > all 1s from (n/2,0) to (n,0). 
>>> >> 
>>> >> > On Thu, Jan 17, 2013 at 9:28 PM, Don <[email protected]> wrote: 
>>> >> > > The downside is that it uses a bunch of extra space. 
>>> >> > > The upside is that it is pretty fast. It only does the 
>>> time-consuming 
>>> >> > > task of scanning the matrix for contiguous pixels once, it only 
>>> >> > > searches for squares larger than what it has already found, and 
>>> it 
>>> >> > > doesn't look in places where such squares could not be. In 
>>> practice 
>>> >> > > it 
>>> >> > > performs at O(n^2) or better for most inputs I tried. But if you 
>>> are 
>>> >> > > devious you can come up with an input which takes longer. 
>>> >> > > Don 
>>> >> 
>>> >> > > On Jan 17, 10:14 am, marti <[email protected]> wrote: 
>>> >> > > > awesome solution Don . Thanks. 
>>> >> 
>>> >> > > > On Thursday, January 17, 2013 12:38:35 AM UTC+5:30, marti 
>>> wrote: 
>>> >> 
>>> >> > > > > Imagine there is a square matrix with n x n cells. Each cell 
>>> is 
>>> >> > > > > either 
>>> >> > > > > filled with a black pixel or a white pixel. Design an 
>>> algorithm 
>>> >> > > > > to 
>>> >> > > find the 
>>> >> > > > > maximum subsquare such that all four borders are filled with 
>>> >> > > > > black 
>>> >> > > pixels; 
>>> >> > > > > optimize the algorithm as much as possible 
>>> >> 
>>> >> > > -- 
>>> > 
>>> > -- 
>>> > 
>>> > 
>>> > 
>>>
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