带噪图像中含障碍物的裸片边缘轮廓检测问题求助

我正尝试检测图像中的裸片（die）边缘轮廓，但图像右上角存在一处障碍物，导致当前检测结果不符合预期。

import numpy as np
import cv2
import time
import glob
import os

def process_img(img):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (15, 15), 1)
    ret, th1 = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
    
    #th1 = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 17, 2)

    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
    th1 = cv2.morphologyEx(th1, cv2.MORPH_OPEN, kernel)
    th1 = cv2.morphologyEx(th1, cv2.MORPH_CLOSE, kernel)

    edge = cv2.Canny(th1, 150, 255)
    return th1, img, edge


def get_roi(img, binary):
    """
    img: source pic
    binary: canny
    """
    # 寻找轮廓
    contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    max_area = 0
    temp = 0
    for cnt in range(len(contours)):
        xxx = cv2.contourArea(contours[cnt])
        if xxx > max_area:
            max_area = xxx
            temp = cnt

    series = contours[temp]
    x, y, w, h = cv2.boundingRect(series)
    p = cv2.arcLength(series, True)
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
    cv2.drawContours(img, [series], 0, (255, 0, 255), 2)

    return img


def die_select(img: np.ndarray, img_template: np.ndarray = None) -> np.ndarray:
    th1, img, edge = process_img(img)
    img = get_roi(img, edge)
    return img

内容的提问来源于stack exchange，提问作者cadd9