I want to detect joints in a sugarcane stick and do not want the border lines to be detected this is my original Original Image, and after applying Morphological Gradient I got this output image. The desired output that I need is to detect only vertical edges that is the joints, the desired output are only the red lines in this image.
So, it would be great if anyone could help me out!
You can try to enhance the following code to find vertical edges as you need
img = cv2.imread("edges.png")
mask = img[:,:,0]
height, width = mask.shape
mask = cv2.threshold(mask, 100, 255, cv2.THRESH_BINARY)[1]
#cv2.imshow("mask", mask)
vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, height//30))
vertical_lines = cv2.erode(mask, vertical_kernel, iterations=1)
vertical_lines = cv2.dilate(vertical_lines, vertical_kernel, iterations=1)
#cv2.imshow("vertical_lines", vertical_lines)
img[vertical_lines > 0, 2] = 255
cv2.imshow("img", img)
cv2.waitKey(0)
SUGARCAN BUD DETECTION & CUTTING MECHANISM
Finally I got the right and working answer for my question, It detects the buds using HOG Circle Transform and shows red circle around it.
It also passes a serial info to the COM4 port of the computer so that the cutter can be operated at the right time.
The program is used to Identify, Detect And Cut a sugarcane bud without human interference
Here's a link to my research paper - https://www.irjet.net/archives/V10/i6/IRJET-V10I627.pdf
import cv2
import numpy as np
import serial
import time
import threading
ser = serial.Serial('COM4',bytesize=8, baudrate=9600, timeout=1) # Replace 'COM3' with the appropriate serial port
time.sleep(3)
cap = cv2.VideoCapture(0)
circle_detected = False
flag = False
def callback():
global flag
flag = True
while True:
# Capture frame-by-frame
ret, frame = cap.read()
# Convert frame to grayscale
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Apply Gaussian blur to remove noise
blur = cv2.GaussianBlur(gray, (5, 5), 0)
# Detect circles using Hough Circle Transform
circles = cv2.HoughCircles(blur, cv2.HOUGH_GRADIENT, 1, 20,
param1=60, param2=34, minRadius=10, maxRadius=50)
# Draw circles around detected centers and set flag if circle is detected
if circles is not None:
circle_detected = True
circles = np.round(circles[0, :]).astype("int")
for (x, y, r) in circles:
cv2.circle(frame, (x, y), r, (0, 0, 255), 2)
if circle_detected:
if threading.active_count() <= 1:
timer = threading.Timer(7.0, callback)
timer.start()
if circle_detected and flag:
flag = False
ser.write(b'00000001')
print("Sent data to serial port")
circle_detected = False
# Display the resulting frame
cv2.imshow('Sugarcane Buds Detection', frame)
# Exit program when 'q' is pressed
if cv2.waitKey(1) == ord('q'):
break
# Release the capture
cap.release()
cv2.destroyAllWindows()
# Flag signal if circle is detected
if circle_detected:
print("Circle detected!")
else:
print("No circle detected.")