diff --git a/exp/hough.py b/exp/hough.py
--- a/exp/hough.py
+++ b/exp/hough.py
@@ -7,100 +7,31 @@ import logging as log
 
 import numpy as np
 import scipy.optimize
+import scipy.signal
 import cv2 as cv
 
-from geometry import Line
 from analyzer.epoint import EPoint
 
 DEBUG=True
 
 
-class BaseHough:
-	def __init__(self,width,height):
-		self._diagLen=int(np.sqrt(height**2+width**2))+1
-		self._center=(width//2,height//2)
-		self._acc=np.zeros((180,self._diagLen),dtype=np.int32)
-
-	def update(self,x,y,weight=1):
-		""":param x: number, 0 <= x < width
-		:param y: number, 0 <= y < height"""
-		for alphaDeg in range(0,180):
-			d=self._computeDist(x,y,alphaDeg)+self._diagLen//2
-			self._acc[(alphaDeg,d)]+=weight
-
-	def extract(self,n):
-		shift=self._diagLen//2
-		peaks=sorted(list(findPeaks(self._acc)),key=lambda rc: self._acc[rc],reverse=True)
-		peaks=self._filterClose(peaks)[:n]
-		log.debug("detected peaks: %s",[(alpha,d-shift) for (alpha,d) in peaks])
+class LineBag:
+	def __init__(self):
+		self._lines=[]
 
-		img=self._createImg()
-		img=self._markPeaks(img,self._filterClose(peaks))
-		self.show(img)
-
-		res=[]
-		for (alphaDeg,d) in peaks:
-			alphaRad=alphaDeg*math.pi/180
-			baseLine=Line(alphaRad,0)
-			dd=baseLine.distanceTo(EPoint(*self._center)) # to shift d from the center to 0,0
-			res.append(Line(alphaRad, dd+d-shift))
-		log.debug("detected lines: %s",res)
-		return res
-
-	def _computeDist(self,x,y,alphaDeg):
-		"""Compute the distance of a line with the provided alphaDeg declination and passing the (x,y) point to the image center.
-		The returned distance might be negative (meaning the angle is in fact alpha+180)."""
-		alphaRad=alphaDeg*math.pi/180
-		(x0,y0)=self._center
-		(dx,dy)=(x-x0,y-y0)
-		d=dx*math.cos(alphaRad)+dy*math.sin(alphaRad)
-		return round(d)
+	def put(self,score,alpha,beta):
+		self._lines.append((score,alpha,beta))
 
-	def _filterClose(self,peaks): # a naive implementation
-		"""Discard points with Euclidean distance on the original image lower than 10.
-		From such pairs keep only the one with a higher value in the accumulator.
-		This can delete a series of points. If a-b and b-c are close and a>b>c, only a is kept."""
-		minDist=13
-		center=EPoint(*self._center)
+	def pull(self,count):
+		self._lines.sort(reverse=True)
 		res=[]
-		for (alphaDeg,d) in peaks:
-			alphaRad=alphaDeg*math.pi/180
-			point=EPoint.fromPolar((alphaRad,d),center)
-			ctrl=True
-			for (betaDeg,e) in peaks:
-				betaRad=betaDeg*math.pi/180
-				point_=EPoint.fromPolar((betaRad,e),center)
-				if point.dist(point_)<minDist and self._acc[(alphaDeg,d)]<self._acc[(betaDeg,e)]:
-					ctrl=False
-			if ctrl: res.append((alphaDeg,d))
+		for (score,alpha,beta) in self._lines:
+			if any(abs(alpha-gamma)<10 and abs(beta-delta)<10 for (_,gamma,delta) in res): continue
+			if any((beta-delta)!=0 and (alpha-gamma)/(beta-delta)<0 for (_,gamma,delta) in res): continue
+			res.append((score,alpha,beta))
+			if len(res)>=count: break
 		return res
 
-	def show(self,img=None):
-		if not DEBUG: return
-		if img is None: img=self._createImg()
-
-		show(img,"Hough transform accumulator")
-
-	def _createImg(self):
-		maxVal=self._acc.max()
-		arr=np.expand_dims(np.uint8(255*self._acc//maxVal),axis=2)
-		img=np.concatenate((arr,arr,arr),axis=2)
-
-		(h,w)=img.shape[:2]
-
-		for x in range(0,w,4): # y axis
-			img[h//2,x]=[255,255,255]
-		for y in range(0,h,4):
-			img[y,w//2]=[255,255,255]
-
-		return img
-
-	def _markPeaks(self,img,peaks):
-		colors=[[255,0,0],[255,255,0],[0,255,0],[0,255,255],[0,0,255]]
-		for (i,(alpha,d)) in enumerate(peaks[:38]):
-			cv.drawMarker(img,(d,alpha),colors[i//9],cv.MARKER_TILTED_CROSS)
-		return img
-
 
 class HoughTransform:
 	def __init__(self,img):
@@ -114,26 +45,13 @@ class HoughTransform:
 		self.update(img)
 
 	def extract(self):
-		shift=self._diagLen//2
-		allPeaks=sorted(list(findPeaks(self._acc)),key=lambda rc: self._acc[rc],reverse=True)
-		peaks=allPeaks[:38]
-		peaks=[(alpha,d-shift) for (alpha,d) in peaks]
-		peaks=self._filterClose(peaks)
-		peaks.sort(key=lambda rc: rc[0])
-		log.debug("detected peaks: %s",peaks)
+		img=self._createImg()
+		(ab,cd)=self._detectLines()
+		for (score,alpha,beta) in (ab,cd):
+			log.debug("score: %s",score)
+			log.debug("alpha, beta: %s, %s",alpha,beta)
+			cv.line(img,(0,alpha),(self._diagLen-1,beta),(0,255,255))
 
-		h2=BaseHough(self._diagLen,180+90)
-		for (alpha,d) in peaks:
-			h2.update(d+shift,alpha)
-			if alpha<90:
-				h2.update(shift-d,alpha+180)
-		lines=h2.extract(3)
-
-		img=self._createImg()
-		img=self._markPeaks(img,self._filterClose(allPeaks[:38]))
-
-		for (i,line) in enumerate(lines):
-			self.drawLine(img,line,i)
 		self.show(img)
 
 	def update(self,img,weight=1):
@@ -192,6 +110,28 @@ class HoughTransform:
 		log.debug("dominant angles: %s, %s",alpha,beta)
 		return (alpha[0],beta[0])
 
+	def _detectLines(self):
+		bag=LineBag()
+		for alpha in range(0,180,2):
+			for beta in range(alpha-45,alpha+45,2):
+				accLine=self._readLine(alpha,beta)
+				(peaks,props)=scipy.signal.find_peaks(accLine,prominence=0)
+				prominences=sorted(props["prominences"],reverse=True)[:19]
+				bag.put(sum(prominences),alpha,beta)
+		return bag.pull(2)
+
+	def _readLine(self,alpha,beta):
+		n=self._diagLen-1
+		res=[]
+		for i in range(n+1):
+			k=round((alpha*(n-i)+beta*i)/n)
+			if k<0 or k>=180:
+				if k<-180 or k>360: print(alpha,beta,i,k)
+				k=k%180
+				i=n+1-i
+			res.append(self._acc[k][i])
+		return res
+
 	def _computeGridParams(self,lines):
 		log.debug("computing grid parameters for: %s",lines)
 		angles=[alpha for (alpha,d) in lines]