Drone Feedback: Object Detection / Color Detection [closed]

I have been working on a code where an A.R Drone 2.0 will detect color and put a red dot in the middle of the image. I am using streaming for the drone. The goal is for the drone to detect a white gutter and fly straight over it from one point to the other. Essentially following a line. I noticed when I changed the BGR to 0, 0, 255, I get the entire gutter to be distinguished but it detects white spots as well. Is there to isolate my detection just to see the gutter. Maybe using shapes, once the gutter is detected, put a bounding box. And my finally question is how do I tell my drone to follow the red dot or maybe drawing a line. I looked at python-AR drone libraries but don't know how to apply it.This is my code.

import numpy as np
import cv2

# open the camera
cap = cv2.VideoCapture('tcp://192.168.1.1:5555')

def nothing(x):
pass

cv2.namedWindow('result')

# Starting with 100's to prevent error while masking
h,s,v = 100,100,100
# Creating track bar
cv2.createTrackbar('h', 'result',0,179,nothing)
cv2.createTrackbar('s', 'result',0,255,nothing)
cv2.createTrackbar('v', 'result',0,255,nothing)

while True:
#read the image from the camera
#You will need this later
frame = cv2.cvtColor(frame, 35)

#converting to HSV

hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
# get info from track bar and appy to result
h = cv2.getTrackbarPos('h','result')
s = cv2.getTrackbarPos('s','result')
v = cv2.getTrackbarPos('v','result')

lower_blue = np.array([h,s,v])
upper_blue = np.array([180,255,255])

cv2.imshow('result',result)
#find center
center=None

if len(cnts)>0:
c=max(cnts, key=cv2.contourArea)
M=cv2.moments(c)
center=(int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
cv2.circle(frame, center,5,(0,0,255),-1)

# color detection limits
lB = 5
lG = 50
lR = 50
hB = 15
hG = 255
hR = 255
lowerLimits = np.array([lB, lG, lR])
upperLimits = np.array([hB, hG, hR])
# Our operations on the frame come here
thresholded = cv2.inRange(frame, lowerLimits, upperLimits)
outimage = cv2.bitwise_and(frame, frame, mask = thresholded)
cv2.imshow('original', frame)
# Display the resulting frame
cv2.imshow('processed',outimage)

# Quit the program when Q is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break

# When everything done, release the capture
print 'closing program'
cap.release()
cv2.destroyAllWindows()