如何从图像中删除非常小的物体[关闭]

Question

我正在将图像预处理到我的新计算机视觉模型。我一直在尝试找到从图像中删除小物体的最佳解决方案，但没有一个有效。

首先，我决定删除宽度或高度小于 80 且大于 400 的对象。它对某些图像有效，但该解决方案不够通用。现在我想删除大于 400 的对象，然后删除面积小于最大和最小面积差值 25% 的对象。不知怎的，它不起作用。感觉它没有标记那些非常小的区域：

label_image = morphology.label(filled_image)
filtered_image = np.copy(filled_image)
regions = measure.regionprops(label_image)
for region in regions:
    if region.solidity < 0.85:
        filtered_image_statistic[label_image == region.label] = 0
    max_size = 400
    if region.bbox[2] - region.bbox[0]  > max_size or  region.bbox[3] - region.bbox[1] > max_size:
        filtered_image_statistic[label_image == region.label] = 0      
    min_row, min_col, max_row, max_col = region.bbox
    if min_row < 10 or min_col < 10 or max_row > image_height - 10 or max_col > image_width - 10:
        filtered_image_statistic[label_image == region.label] = 0
        
labeled_image = morphology.label(filtered_image)
regions = measure.regionprops(labeled_image)
regions_areas = [region.area for region in regions]
test = max(regions_areas) - min(regions_areas)
print(f"{test}, {max(regions_areas)}, {min(regions_areas)}")
for region in regions:
    print(region.area)
    if region.area <= 0.25*test:
        filtered_image_statistic[labeled_image == region.label] = 0
 
show_image(filtered_image_statistic) 

Answer 1

import cv2
import numpy as np
from skimage import morphology

def remove_small_objects(image, min_size):
    # Convert the image to grayscale
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    # Threshold the image (you may need to adjust the threshold value)
    _, binary = cv2.threshold(gray, 128, 255, cv2.THRESH_BINARY)

    # Remove small objects using morphological operations
    binary = morphology.remove_small_objects(binary, min_size)

    # Apply inverse threshold
    binary = cv2.bitwise_not(binary)

    # Apply the mask to the original image
    result = cv2.bitwise_and(image, image, mask=binary)

    return result

# Load your image
image = cv2.imread('your_image.jpg')

# Define the minimum size of objects to keep
min_size = 100  # Adjust this value based on your needs

# Remove small objects
result_image = remove_small_objects(image, min_size)

# Save the result
cv2.imwrite('result_image.jpg', result_image)