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Having problem in detecting feet pronation in foot scan image, I tried to mark pressure point based on threshold and able to get some results, but this technique failed in those images in which feet color is dark. Result of what I have tried is Here but I want the final result looks like these Feet Image Results.

Any help/suggestion will be appreciated.
Thanks

Edit
I have added the scan image of hand in which pressure points are circled and processed image supposed to detect only pressure point but it failed based on color of skin as I mentioned above. I'm applying color threshold. The image which in which detection failed is Here

There is not enough color differences to do this easily. I tried by increasing contrast and converting to HSV colorspace (info - opencv), which makes selecting colors easier.

Result:

# load image

img = cv2.imread("hand.png")



#increase contrast

new_image = np.zeros(img.shape, img.dtype)

alpha = 4 # Simple contrast control

beta = -300    # Simple brightness control

for y in range(img.shape[0]):

    for x in range(img.shape[1]):

        for c in range(img.shape[2]):

            new_image[y,x,c] = np.clip(alpha*img[y,x,c] + beta, 0, 255)



# convert to HSV

hsv = cv2.cvtColor(new_image, cv2.COLOR_BGR2HSV) 

# set lower and upper color limits

lower_val = np.array([30,0,200])

upper_val = np.array([75,240,255])

# Threshold the HSV image 

mask = cv2.inRange(hsv, lower_val, upper_val)

# remove noise

kernel =  np.ones((3,3),np.uint8)

mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)



# select whole hand

# set lower and upper color limits

lower_val = np.array([0,0,100])

upper_val = np.array([179,255,255])

# Threshold the HSV image 

mask2 = cv2.inRange(hsv, lower_val, upper_val)



# create a mask that has the whole hand, but not the prssure points

mask_combined = cv2.bitwise_xor(mask, mask2)

# Create a copy of the image

image = img.copy()

# Fill copy image with a blue-green-ish color

image[:] = (150, 150, 20)

# use the combined mask to color in upressured area's of the hand

res2 = cv2.bitwise_and(image,image, mask= mask_combined)

# Fill copy image with red color(set each pixel to red)

image[:] = (20, 20, 205)

# use the pressure mask to color in pressured area's

res = cv2.bitwise_and(image,image, mask= mask)

# combine colored images

final = dst = cv2.add(res2,res)

#show image

cv2.imshow("img", img)

cv2.imshow("result", final)

cv2.imshow("mask", mask)

cv2.imshow("mask2", mask_combined)

cv2.waitKey(0)

cv2.destroyAllWindows()      

Note: I cropped the image you provided, if you have the full image the result may improve by tweaking the colorlimits and the morphology - read about it here