如何分割彎曲杆進行角度計算？

我試圖使用OpenCV從它的背景中分割一個彎曲杆，然後找到彎曲並計算每個彎曲之間的角度。如何分割彎曲杆進行角度計算？

第一部分幸運的是前景和背景之間足夠的對比度是微不足道的。當分割時，一點腐蝕/膨脹照顧反射/高光。

第二部分是我不知道如何處理它的地方。

我可以很容易地檢索輪廓（頂部和底部非常相似，所以要麼），但我似乎無法弄清楚如何將輪廓分割成直線部分和彎曲杆來計算角度。

到目前爲止，我已經嘗試過簡單地繪製輪廓，但是要麼我得到太多或太少的點，並且難以指定正確的設置以保持筆直部分筆直並且彎曲部分簡化。

這裏是我的輸入圖像（bend.png）

而且這裏是我試過到目前爲止：

#!/usr/bin/env python 
import numpy as np 
import cv2 

threshold = 229 
# erosion/dilation kernel 
kernel = np.ones((5,5),np.uint8) 
# contour simplification 
epsilon = 0 

# slider callbacks 
def onThreshold(x): 
    global threshold 
    print "threshold = ",x 
    threshold = x 
def onEpsilon(x): 
    global epsilon 
    epsilon = x * 0.01 
    print "epsilon = ",epsilon 

# make a window to add sliders/preview to 
cv2.namedWindow('processed') 
#make some sliders 
cv2.createTrackbar('threshold','processed',60,255,onThreshold) 
cv2.createTrackbar('epsilon','processed',1,1000,onEpsilon) 
# load image 
img = cv2.imread('bend.png',0) 
# continuously process for quick feedback 
while 1: 
    # exit on ESC key 
    k = cv2.waitKey(1) & 0xFF 
    if k == 27: 
     break 

    # Threshold 
    ret,processed = cv2.threshold(img,threshold,255,0) 
    # Invert 
    processed = (255-processed) 
    # Dilate 
    processed = cv2.dilate(processed,kernel) 
    processed = cv2.erode(processed,kernel) 
    # Canny 
    processed = cv2.Canny(processed,100,200) 

    contours, hierarchy = cv2.findContours(processed,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) 
    if len(contours) > 0: 
     approx = cv2.approxPolyDP(contours[0],epsilon,True) 
     # print len(approx) 
     cv2.drawContours(processed, [approx], -1, (255,255,255), 3) 
     demo = img.copy() 
     cv2.drawContours(demo, [approx], -1, (192,0,0), 3) 
    # show result 
    cv2.imshow('processed ',processed) 
    cv2.imshow('demo ',demo) 


# exit 
cv2.destroyAllWindows()

這裏就是我這麼遠，但我不相信這是最好的辦法：

我試圖在視覺上弄清楚了這一點，我所針對的是沿着這些路線的東西：

因爲最終的目標是計算彎曲部分的東西之間的夾角像這種感覺簡單：

我的假設是對INT之間的擬合直線和計算的角度ersecting線可以工作：

我沒有使用HoughLines OpenCV Python tutorial快速測試，但無論是參數的傳遞，我沒有得到很大的成績：

#!/usr/bin/env python 
import numpy as np 
import cv2 

threshold = 229 
minLineLength = 30 
maxLineGap = 10 
houghThresh = 15 

# erosion/dilation kernel 
kernel = np.ones((5,5),np.uint8) 

# slider callbacks 
def onMinLineLength(x): 
    global minLineLength 
    minLineLength = x 
    print "minLineLength = ",x 

def onMaxLineGap(x): 
    global maxLineGap 
    maxLineGap = x 
    print "maxLineGap = ",x 

def onHoughThresh(x): 
    global houghThresh 
    houghThresh = x 
    print "houghThresh = ",x 

# make a window to add sliders/preview to 
cv2.namedWindow('processed') 
#make some sliders 
cv2.createTrackbar('minLineLength','processed',1,50,onMinLineLength) 
cv2.createTrackbar('maxLineGap','processed',5,30,onMaxLineGap) 
cv2.createTrackbar('houghThresh','processed',15,50,onHoughThresh) 
# load image 
img = cv2.imread('bend.png',0) 
# continuously process for quick feedback 
while 1: 
    # exit on ESC key 
    k = cv2.waitKey(1) & 0xFF 
    if k == 27: 
     break 

    # Threshold 
    ret,processed = cv2.threshold(img,threshold,255,0) 
    # Invert 
    processed = (255-processed) 
    # Dilate 
    processed = cv2.dilate(processed,kernel) 
    processed = cv2.erode(processed,kernel) 
    # Canny 
    processed = cv2.Canny(processed,100,200) 

    lineBottom = np.zeros(img.shape,np.uint8) 

    contours, hierarchy = cv2.findContours(processed,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) 
    if len(contours) > 0: 
     cv2.drawContours(lineBottom, contours, 0, (255,255,255), 1) 

    # HoughLinesP 
    houghResult = img.copy() 
    lines = cv2.HoughLinesP(lineBottom,1,np.pi/180,houghThresh,minLineLength,maxLineGap) 
    try: 
     for x in range(0, len(lines)): 
      for x1,y1,x2,y2 in lines[x]: 
       cv2.line(houghResult,(x1,y1),(x2,y2),(0,255,0),2) 
    except Exception as e: 
     print e 

    # show result 
    cv2.imshow('lineBottom',lineBottom) 
    cv2.imshow('houghResult ',houghResult) 


# exit 
cv2.destroyAllWindows()