Algorithm 1	Top K Search
Require:	database of fingerprints $\overrightarrow{B}$ binned by bit count Bs
Ensure:	hits contains top K hits which satisfy Similarity($\overrightarrow{A},\overrightarrow{B}$) > T
1:	hits ← MinHeap()
2:	bounds ← List()
3:	for all B in database do //iterate over bins
4:	tuple ← Tuple(Bound(A,B),B)
5:	ListAppend(bounds, tuple)
6:	end for
7:	Quicksort(bounds) //NOTE: the length of bounds is constant
8:	for all bound, B in bounds do //iterate in order of decreasing bound
9:	if bound < T then
10:	break //threshold stopping condition
11:	end if
12:	if K ≤ HeapSize(hits) and bound <MinSimilarity(hits) then
13:	break //top-K stopping condition
14:	end if
15:	for all $\overrightarrow{B}$ in database[B] do
16:	S=Similarity($\overrightarrow{A},\overrightarrow{B}$)
17:	tuple ← Tuple(S,$\overrightarrow{B}$)
18:	if S ≤ T then
19:	continue //ignore this $\overrightarrow{B}$ and continue to next
20:	else if Length(hits)< K then
21:	HeapPush(hits, tuple)
22:	else if S > MinSimilarity(hits) then
23:	HeapPopMin(hits)
24:	HeapPush(hits,tuple)
25:	end if
26:	end for
27:	end for
28:	return hits