熵解似乎有问题并且计算过于密集。为什么不进行边缘检测？
我刚刚编写了这段 python 代码来为自己解决同样的问题。我的背景是肮脏的白色，所以我使用的标准是黑暗和颜色。我简化了这个标准，只取每个像素的 R、B 或 B 值中的最小值，这样黑色或饱和红色都一样突出。我还使用了每行或每列的最暗像素的平均值。然后我从每一个边缘开始，努力进入，直到跨过门槛。
这是我的代码：
#these values set how sensitive the bounding box detection is
threshold = 200 #the average of the darkest values must be _below_ this to count (0 is darkest, 255 is lightest)
obviousness = 50 #how many of the darkest pixels to include (1 would mean a single dark pixel triggers it)
from PIL import Image
def find_line(vals):
#implement edge detection once, use many times
for i,tmp in enumerate(vals):
tmp.sort()
average = float(sum(tmp[:obviousness]))/len(tmp[:obviousness])
if average <= threshold:
return i
return i #i is left over from failed threshold finding, it is the bounds
def getbox(img):
#get the bounding box of the interesting part of a PIL image object
#this is done by getting the darekest of the R, G or B value of each pixel
#and finding were the edge gest dark/colored enough
#returns a tuple of (left,upper,right,lower)
width, height = img.size #for making a 2d array
retval = [0,0,width,height] #values will be disposed of, but this is a black image's box
pixels = list(img.getdata())
vals = [] #store the value of the darkest color
for pixel in pixels:
vals.append(min(pixel)) #the darkest of the R,G or B values
#make 2d array
vals = np.array([vals[i * width:(i + 1) * width] for i in xrange(height)])
#start with upper bounds
forupper = vals.copy()
retval[1] = find_line(forupper)
#next, do lower bounds
forlower = vals.copy()
forlower = np.flipud(forlower)
retval[3] = height - find_line(forlower)
#left edge, same as before but roatate the data so left edge is top edge
forleft = vals.copy()
forleft = np.swapaxes(forleft,0,1)
retval[0] = find_line(forleft)
#and right edge is bottom edge of rotated array
forright = vals.copy()
forright = np.swapaxes(forright,0,1)
forright = np.flipud(forright)
retval[2] = width - find_line(forright)
if retval[0] >= retval[2] or retval[1] >= retval[3]:
print "error, bounding box is not legit"
return None
return tuple(retval)
if __name__ == '__main__':
image = Image.open('cat.jpg')
box = getbox(image)
print "result is: ",box
result = image.crop(box)
result.show()
