I have been tasked with taking scanned images of a petri dish with bacterial colonies growing on it over time and performing an analysis of different statistics such as growth rate, time of appearance, etc. Thus far, I have taken the scanned image;
converted it to grayscale, ran it through a median filter, and thresholded it to arrive at this result;
The following snippet of code is my progress thus far:
# Reading image and gray scaling
test = skimage.io.imread("C:/Users/user/Documents/PythTestImg/img016.tif")
graytest = skimage.color.rgb2gray(test)
fig, ax = plt.subplots()
plt.imshow(graytest, cmap='gray')
plt.show()
# Median filter
d = disk(radius=2)
blurredtest = skimage.filters.median(graytest, d)
fig, ax = plt.subplots()
plt.imshow(blurredtest, cmap='gray')
plt.show()
# Histogram creation
histogram, bin_edges = np.histogram(blurredtest, bins=256, range=(0.0, 1.0))
fig, ax = plt.subplots()
plt.plot(bin_edges[0:-1], histogram)
plt.title("Grayscale Histogram")
plt.xlabel("grayscale value")
plt.ylabel("pixels")
plt.xlim(0, 1.0)
plt.show()
# Thresholding section
#t = skimage.filters.threshold_otsu(blurredtest)
#print("Found automatic threshold t = {}.".format(t))
t = 0.93
finaltest = blurredtest > t
fig, ax = plt.subplots()
plt.imshow(finaltest, cmap="gray")
plt.show()
This seems promising because I have completely isolated the bacterial colonies (shown in white) from the rest of the image; however, as you can see, there are some "false positives" on the perimeter of the circle that I need to remove, the big chunk of white on the perimeter more specifically. I have spoken with colleagues, and they suggested that I manually delete these values in the image matrix but this does not seem practical as my end goal is to process many images efficiently. Is there a way to selectively remove the perimeter while keeping the colonies intact? I am working on PyCharm using Python 3.11 with scikit-image for my image processing needs.
I have attempted to use hough transform functions and edge detection, but it does not find the correct parameters and returns the same result that I inputted to the functions. I am also confused about the input of parameters to these functions so that may be a reason for not being able to return what I want.
