Klusmo

import numpy as np
import matplotlib.pyplot as plt


# erosion of a img with a structuring element
def erosion(img, struct_element):
    # get the image and structuring element dimensions
    x_img, y_img = img.shape
    x_struct, y_struct = struct_element.shape
    struct_center = (x_struct // 2, y_struct // 2)

Klusmo

import numpy as np
import matplotlib.pyplot as plt


def convolve2D(image, kernel):
    # Flip the kernel
    kernel = np.flipud(np.fliplr(kernel))

    # Get the image and kernel dimensions
    x_kern, y_kern = kernel.shape

Klusmo

import numpy as np
import cv2
import matplotlib.pyplot as plt


def histogram(img):
    hist = np.zeros(256)
    for i in range(img.shape[0]):
        for j in range(img.shape[1]):
            hist[img[i, j]] += 1

Klusmo

import numpy as np
import cv2
import matplotlib.pyplot as plt


def linear_transform(img, i1, i2, k1: int, k2: int):
    new_img = np.zeros(img.shape, dtype=np.uint8)

    rows, cols = img.shape
    for row in range(rows):

Klusmo

# Função do laboratório 4

def f1(x):
    return 7*(x - 1)

def f2(x):
    return 7 * 256 * (x - 1)

def f3(x):