Hand posture detection with OpenCV #8

rainyear · 2015-07-03T10:35:17Z

简单的手势识别，基本思路是基于皮肤检测，皮肤的颜色在HSV颜色空间下与周围环境的区分度更高，从RGB转换到HSV颜色空间下针对皮肤颜色进行二值化，得到mask：

def HSVBin(img):
    hsv = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)

    lower_skin = np.array([100, 50, 0])
    upper_skin = np.array([125, 255, 255])

    mask = cv2.inRange(hsv, lower_skin, upper_skin)
    # res = cv2.bitwise_and(img, img, mask=mask)
    return mask

然后通过腐蚀与膨胀等形态学变化去除一些噪点，得到更完整的白色（皮肤）色块，最后找出色块的轮廓，并通过色块大小排除一些面积较小的噪点：

def getContours(img):
    kernel = np.ones((5,5),np.uint8)
    closed = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)
    closed = cv2.morphologyEx(closed, cv2.MORPH_CLOSE, kernel)
    contours, h  = cv2.findContours(closed, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    validContours = [];
    for cont in contours:
        if cv2.contourArea(cont) > 9000:
            # x,y,w,h = cv2.boundingRect(cont)
            # if h/w > 0.75: # filter face failed
            validContours.append(cv2.convexHull(cont))
            # rect = cv2.minAreaRect(cont)
            # box = cv2.cv.BoxPoints(rect)
            # validContours.append(np.int0(box))
    return validContours