diff --git a/geometry_extraction/gate1.png b/geometry_extraction/gate1.png
new file mode 100644
index 0000000..1c33874
Binary files /dev/null and b/geometry_extraction/gate1.png differ
diff --git a/geometry_extraction/line_detection.py b/geometry_extraction/line_detection.py
index a53c62e..ce82cf2 100644
--- a/geometry_extraction/line_detection.py
+++ b/geometry_extraction/line_detection.py
@@ -1,6 +1,95 @@
+import numpy as np
+import cv2 as cv
+
 def main():
-    pass
+    #Duplicating colour filtering code for now, will change to pass image through funciton
+    # Read image
+    img = cv.imread("gate1.png")
+
+    # Convert RGB to HSV (makes creating range of colour easier)
+    hsv_img = cv.cvtColor(img, cv.COLOR_BGR2HSV)
+
+    # Define Colour Range
+    lower_orange = np.array([0, 0, 50])
+    upper_orange = np.array([18, 200, 255])
+
+    # Create mask
+    mask = cv.inRange(hsv_img, lower_orange, upper_orange)
+
+    #Create minimum area bounding box for mask
+    contours, hierarchy = cv.findContours(mask, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
+    rect = cv.minAreaRect(contours[-1])
+    box = cv.boxPoints(rect)
+    box = np.int0(box)
+
+    #Create skeleton of mask
+    mask = cv.GaussianBlur(mask, (17, 17), 0)
+    kernel = np.ones((20, 20), np.uint8)
+    mask = cv.erode(mask, kernel, iterations=2)
+    size = np.size(mask)
+    skel = np.zeros(mask.shape, np.uint8)
+    element = cv.getStructuringElement(cv.MORPH_CROSS, (3, 3))
+    done = False
+
+    while (not done):
+        eroded = cv.erode(mask, element)
+        temp = cv.dilate(eroded, element)
+        temp = cv.subtract(mask, temp)
+        skel = cv.bitwise_or(skel, temp)
+        mask = eroded.copy()
+        zeros = size - cv.countNonZero(mask)
+        if zeros == size:
+            done = True
+
+    #Generate Hough lines from skeleton
+    edges = cv.Canny(skel, 250, 250)
+    lines = cv.HoughLinesP(edges, rho=1, theta=np.radians(1), threshold=100, maxLineGap=500)
+
+    dists = []
+    for line in lines:
+        x1, y1, x2, y2 = line[0]
+        a = np.array((x1, y1))
+        b = np.array((x2, y2))
+        dist = np.linalg.norm(a-b)
+        dists.append(dist)
+
+    #Determine largest hough line generated
+    largestLine = dists.index(max(dists))
+
+    #Extend largest hough line and find intersection with minimum area bounding box
+    m1 = (lines[largestLine][0][1] - lines[largestLine][0][3])/(lines[largestLine][0][0] - lines[largestLine][0][2])
+    m2 = (box[0][1] - box[3][1])/(box[0][0] - box[3][0])
+    m3 = (box[1][1] - box[2][1])/(box[1][0] - box[2][0])
+    b1 = lines[largestLine][0][1] - (m1*lines[largestLine][0][0])
+    b2 = box[0][1] - (m2*box[0][0])
+    b3 = box[1][1] - (m3*box[1][0])
+
+    x1 = (b2-b1)/(m1-m2)
+    x2 = (b3-b1)/(m1-m3)
+    y1 = (m1*x1) + b1
+    y2 = (m1*x2) + b1
+
+    #Check if any point is going out of frame
+    if x1 < 0:
+        x1 = 0
+    if x2 < 0:
+        x2 = 0
+    if y1 < 0:
+        y1 = 0
+    if y2 < 0:
+        y2 = 0
+
+    #Print coordinates of line
+    print(x1, y1, x2, y2)
+
+    #Draw line
+    cv.line(img, (int(x1), int(y1)), (int(x2), int(y2)), (0, 255, 0), 3)
+
+    #Show resulting image with line detected
+    cv.imshow("Image", img)
 
+    cv.waitKey(0)
+    cv.destroyAllWindows()
 
 if __name__ == '__main__':
     main()