掌紋辨識

取得掌紋

import cv2

image = cv2.imread("h_test.png")

cv2.imshow("palm",image) #to view the palm in python

cv2.waitKey(0)

#轉換爲灰度

gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)

#Canny Edge Detector的過濾算法來查找掌紋

edges = cv2.Canny(gray,60,65,apertureSize = 3)

cv2.imshow("edges",edges)

cv2.waitKey(0)

#反轉顏色，識別線條是黑色

edges = cv2.bitwise_not(edges)

cv2.imshow("change black and white",edges)

cv2.waitKey(0)

#黑色線條圖像與原始圖像混合

cv2.imwrite("palmlines.jpg", edges)

palmlines = cv2.imread("palmlines.jpg")

img = cv2.addWeighted(palmlines, 0.3, image, 0.7, 0)

cv2.imshow("lines in palm", img)

cv2.waitKey(0)

圖片比對

#用模板圖片去尋找圖片中的物件

import cv2 as cv

import numpy as np

from matplotlib import pyplot as plt

from PIL import Image, ImageDraw, ImageFont

#讀入原圖和模板

image = cv.imread("h_test.png")

img_rgb = cv.imread('palmlines.jpg') #原圖

img_gray = cv.cvtColor(img_rgb, cv.COLOR_BGR2GRAY)

template = cv.imread('p01.jpg',0) #比對用圖

w, h = template.shape[::-1]

# 讓視窗可以自由縮放大小

cv.namedWindow('TEST', cv.WINDOW_NORMAL)

#標準相關模板匹配

res = cv.matchTemplate(img_gray,template,cv.TM_CCOEFF_NORMED)

threshold = 0.4

loc = np.where( res >= threshold) # 匹配程度大於%40的坐標y,x

for pt in zip(*loc[::-1]): # *號表示可選參數

    cv.rectangle(img_rgb, pt, (pt[0] + w, pt[1] + h), (0,255,0), 2)

#cv.rectangle 畫框線

cv.imwrite('res.png',img_rgb)

# 顯示圖片

img = cv.imread('res.png')

#黑色線條圖像與原始圖像混合

img_ok = cv.addWeighted(img, 0.3, image, 0.7, 0)

def cv2ImgAddText(img_ok, text, left, top, textColor=(0, 255, 0), textSize=20):

    if (isinstance(img_ok, np.ndarray)):  #判断是否OpenCV图片类型

        img_ok = Image.fromarray(cv.cvtColor(img_ok, cv.COLOR_BGR2RGB))

    draw = ImageDraw.Draw(img_ok)

    fontText = ImageFont.truetype(

        "font/simsun.ttc", textSize, encoding="utf-8")

    draw.text((left, top), text, textColor, font=fontText)

    return cv.cvtColor(np.asarray(img_ok), cv.COLOR_RGB2BGR)

img_txt = cv2ImgAddText(img_ok, "生命線", pt[0] ,  pt[1]-30 , (255, 0, 0), 20)

cv.imshow('TEST', img_txt)

#imagex = cv.imread("res.png")

#cv.imshow("ok",imagex)

cv.waitKey(0)