在恶劣的照明环境下通过衣服的颜色识别人的问题 [英] issue of the recognize people by their clothes color with not severe illumination environments

问题描述

我对使用真实机器人的人类感兴趣. 我想将衣服的颜色用作关键特征，以识别机器人前面的目标人员来跟随他/她，但由于它的功能很弱，并且照明变化非常简单，因此我感到很痛苦.因此，我需要将此算法更改为另一种算法，或者实时在线更新RGB值，但是我对图像处理的经验不足.

I am interested in the human following using a real robot. I'd like to use the color of clothes as a key feature to identify the target person in front of the robot to follow him/ her but I am suffering due to it is a weak feature with a very simple illumination changing. So, I need to alter this algorithm to another or update values (RGB) online in real-time but I don't have enough experience with image processing.

这是我用于颜色检测的完整代码:

this is my full code for color detection:

import cv2
import numpy as np
from imutils.video import FPS
# capturing video through webcam
import time

cap = cv2.VideoCapture(0)

width = cap.get(3)  # float
height = cap.get(4)  # float
print width, height
time.sleep(2.0)
fps = FPS().start()
while (1):
    _, img = cap.read()

    if _ is True:
        hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    else:
        continue
    # blue color

    blue_lower = np.array([99, 115, 150], np.uint8)
    blue_upper = np.array([110, 255, 255], np.uint8)
    blue = cv2.inRange(hsv, blue_lower, blue_upper)
    kernal = np.ones((5, 5), "uint8")
    blue = cv2.dilate(blue, kernal)
    res_blue = cv2.bitwise_and(img, img, mask=blue)

            # Tracking blue
    (_, contours, hierarchy) = cv2.findContours(blue, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for pic, contour in enumerate(contours):
        area = cv2.contourArea(contour)
        if (area > 300):
            x, y, w, h = cv2.boundingRect(contour)
            img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
            cv2.putText(img, "Blue Colour", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0))
    cv2.imshow("Color Tracking", img)
    if cv2.waitKey(10) & 0xFF == ord('q'):
        cap.release()
        cv2.destroyAllWindows()
        break
    fps.update()

    # stop the timer and display FPS information
    fps.stop()
#    print("[INFO] elapsed time: {:.2f}".format(fps.elapsed()))
#    print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))

这些是输出:

1-通过一个人的衣服颜色识别一个人

1- recognize a person by his clothes color

2-它丢失了，照度变化是一个非常简单而又不严重的

2- it is lost, the illumination changing is a very simple not severe

任何想法或建议将不胜感激

Any ideas or suggestions will be appreciated

推荐答案

看起来确实需要使用一些更高级的颜色相似度函数来处理复杂的情况. Delta E 将是正确的起点.

It does look like you need to use a bit more advanced color similarity function to handle complex cases. Delta E will be the right starting point.

适当的阈值或几种具有相关阈值的颜色将有助于获得非常准确的结果:

Proper threshold or several colors with associated thresholds will help to achieve pretty accurate results:

查看右侧的颜色列表

完整示例.

这篇关于在恶劣的照明环境下通过衣服的颜色识别人的问题的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！