diff --git a/exp/board_detect.py b/exp/board_detect.py
--- a/exp/board_detect.py
+++ b/exp/board_detect.py
@@ -5,6 +5,7 @@ sys.path.append("../src")
 import os
 import math
 import random
+import itertools
 import logging as log
 
 import cv2 as cv
@@ -109,30 +110,21 @@ class BoardDetector:
 		stonesImg=np.zeros((self._rectH,self._rectW),np.uint8)
 		for (point,c) in stones:
 			cv.circle(stonesImg,(int(point.x),int(point.y)),2,255,-1)
-		# cv.drawContours(stonesImg,[c for (point,c) in stones],-1,255,-1)
+
 		show(stonesImg,"detected stones")
 		hough.update(stonesImg,10)
 		lines=hough.extract()
 
 		linesImg=np.copy(rect)
-		for line in lines:
+		for line in itertools.chain(*lines):
 			self._drawLine(linesImg,line)
 		show(linesImg,"detected lines")
 
-		# # detect vanishing points of the lines
-		# imgCenter=EPoint(w//2-x1, h//2-y1)
-		# (a,b,c,d)=(p-EPoint(x1,y1) for p in self._annotations[filename][0])
-		# (p,q,r,s)=(Line(a,b),Line(b,c),Line(c,d),Line(d,a))
-		# v1=p.intersect(r)
-		# v2=q.intersect(s)
-		# log.debug("true vanishing points: %s ~ %s, %s ~ %s",v1,v1.toPolar(imgCenter),v2,v2.toPolar(imgCenter))
-		# vanish=self._detectVanishingPoints(lines,imgCenter,(v1.toPolar(imgCenter),v2.toPolar(imgCenter)))
-		#
 		# # rectify the image
-		# matrix=self._computeTransformationMatrix(vanish,lines)
-		# transformed=cv.warpPerspective(rect,matrix,(self._rectW,self._rectH))
-		#
-		# # determine precise board edges
+		matrix=self._computeTransformationMatrix(lines[0][0],lines[0][-1],lines[1][0],lines[1][-1])
+		transformed=cv.warpPerspective(rect,matrix,(self._rectW,self._rectH))
+
+		# determine precise board edges
 
 	def _detectRough(self,img,filename):
 		corners=self._annotations[filename][0]
@@ -177,36 +169,8 @@ class BoardDetector:
 		show(stones,"black and white areas")
 		return stones
 
-	def _printLines(self,lines,allPoints,img):
-		for (i,line) in enumerate(lines):
-			img_=np.copy(img)
-			points=list(line.getSortedPoints())
-			(a,b)=max(((a,b) for a in points for b in points if a<b),key=lambda ab: ab[0].dist(ab[1]))
-			(xa,ya)=a
-			(xb,yb)=b
-			points.sort(key=lambda p: a.dist(p))
-			cv.line(img_,(int(xa),int(ya)),(int(xb),int(yb)),(255,255,0),1)
-			cv.imwrite("/tmp/{0}.png".format(i),img_)
-			pointDists=",".join(str(round(p1.dist(p2),3)) for (p1,p2) in zip(points[:-1],points[1:]))
-			log.debug("\t".join(map(str,[i,line,line.score(allPoints),pointDists])))
-
-	def _detectVanishingPoints(self,lines,imgCenter,trueVs):
-		polarHough=PolarHough(math.pi/180,10)
-		for (i,ab) in enumerate(lines):
-			for cd in lines[i+1:]:
-				point=ab.intersect(cd)
-				if 0<=point.x<=self._rectW and 0<=point.y<=self._rectH: continue
-				# log.debug("%s -> %s",point,point.toPolar(imgCenter))
-				polarHough.put(point.toPolar(imgCenter))
-		vanish=[EPoint.fromPolar(p,imgCenter) for p in polarHough.extract(2,trueVs)]
-		log.debug(vanish)
-		return vanish
-
-	def _computeTransformationMatrix(self,vanish,lines):
-		(v1,v2)=vanish
-		(p,r)=sorted(lines,key=lambda p: point2lineDistance(p.a,p.b,v1))[:2]
-		(q,s)=sorted(lines,key=lambda p: point2lineDistance(p.a,p.b,v2))[:2]
-		(a,b,c,d)=Corners([p.intersect(q),q.intersect(r),r.intersect(s),s.intersect(p)]) # canonize the abcd order
+	def _computeTransformationMatrix(self,p,q,r,s): # p || q, r || s
+		(a,b,c,d)=Corners([p.intersect(r),p.intersect(s),q.intersect(r),q.intersect(s)]) # canonize the abcd order
 		a_=EPoint(b.x,min(a.y,d.y))
 		b_=EPoint(b.x,max(b.y,c.y))
 		c_=EPoint(c.x,max(b.y,c.y))
@@ -223,7 +187,7 @@ class BoardDetector:
 			cv.drawMarker(rect,(int(point.x),int(point.y)),(0,255,255),cv.MARKER_TILTED_CROSS)
 		show(rect)
 		transformed=cv.warpPerspective(rect,matrix,(self._rectW,self._rectH))
-		show(transformed)
+		show(transformed,"rectified image")
 
 		return matrix
 
diff --git a/exp/hough.py b/exp/hough.py
--- a/exp/hough.py
+++ b/exp/hough.py
@@ -59,11 +59,13 @@ class HoughTransform:
 			log.debug("alpha, beta: %s, %s",alpha,beta)
 			self._drawLine(img,alpha,beta,peaks,i)
 
+			res.append([])
 			keys=self._readLineKeys(alpha,beta)
 			for k in peaks:
 				(alphaDeg,d)=keys[k]
 				line=Line(alphaDeg*math.pi/180,d-self._diagLen//2)
-				res.append(self._transformOutput(line))
+				res[-1].append(self._transformOutput(line))
+			res[-1].sort(key=lambda line: line.d)
 			i+=1
 
 		self.show(img)