How to detect semi transparent logo location on video?

edit

I make python script which auto detect stationary object on video (to simplify the idea - let it be a logo). I don't know logo location, because I can't see video. I start script in console. The idea of script - auto detection, not manual work. But I know that logo is on all video frames, and it located as usual in one of the coner.

I have small test videos:

https://dl.dropbox.com/u/100403694/1.mp4

https://dl.dropbox.com/u/100403694/2.mp4

https://dl.dropbox.com/u/100403694/3.mp4

https://dl.dropbox.com/u/100403694/4.mp4

All tests seems to be done except 2.mp4 Script can't detect logo on video 2.mp4

This is my script. Usage script.py 2.mp4

#!/usr/bin/env python
# -*- coding= utf-8 -*-

import sys
import cv2
import numpy as np
from time import clock

tracked_contours = []

class Contour():
    def __init__(self, contour):
        self.data = get_contour_data(contour)
        self.pixel_error = 5
        self.score = 0

    def __eq__(self, other):
        for i in range(len(self.data)):
            if abs(self.data[i]-other.data[i]) > self.pixel_error:
                return False
        return True

def get_contour_data(contour):
    xx = np.array([ a[0][0] for a in contour ])
    yy = np.array([ a[0][1] for a in contour ])
    return [xx.min(), yy.min(), xx.max(), yy.max()]

def check_contours(contours, count, img):
    for tracked_contour in tracked_contours:
        if count % 2 == 0:
            tracked_contour.score -= 1

        if tracked_contour.score < 0:
            tracked_contours.remove(tracked_contour)

    for contour in contours:
        c = Contour(contour)
        if c in tracked_contours:
            i = tracked_contours.index(c)
            tracked_contours[i].score += 1
            cv2.rectangle(img, (tracked_contours[i].data[0], \
                tracked_contours[i].data[1]), (tracked_contours[i].data[2], \
                tracked_contours[i].data[3]), (tracked_contours[i].score*10, tracked_contours[i].score*5, tracked_contours[i].score), tracked_contours[i].score)
            if tracked_contours[i].score > 40:
                return True, c
        else: tracked_contours.append(c)

    return False, None

def drawContours(contours, img):
    for contour in contours:
        data = get_contour_data(contour)
        cv2.rectangle(img, (data[0], data[1]), (data[2], data[3]), (255,0,0))

def detect(file_name):
    c = cv2.VideoCapture(file_name)
    _,f = c.read()
    f = cv2.cvtColor(f, cv2.COLOR_BGR2GRAY)

    avg = np.float32(f)

    cv2.namedWindow("img")
    cv2.namedWindow("grey")
    cv2.namedWindow("avg")

    t = 0
    count = 0

    while(1):
        if t % 5 != 0:
            _,f = c.read()
            if f == None:
                exit(1)
            t+=1
            continue
        count += 1
        t += 1

        _,f = c.read()

        if f == None:
            exit(1)

        cv2.imshow('img',f)

        f = np.float32(cv2.cvtColor(f, cv2.COLOR_BGR2GRAY))

        cv2.accumulateWeighted(f, avg, 0.005)

        res = cv2.convertScaleAbs(avg)

        cv2.imshow('grey',res)

        thresh, res = cv2.threshold(res, 200, 255, cv2.THRESH_BINARY)
        kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(40,40))
        mat = cv2.dilate(res,kernel)

        contours, hierarchy = cv2.findContours(mat,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_L1)
        res = cv2.cvtColor(res, cv2.COLOR_GRAY2BGR)
        a,b = check_contours(contours, count, res)

        if a == True:
            cv2.rectangle(res, (b.data[0], b.data[1]), (b.data[2], b.data[3]), (0,255,0), 5)
            cv2.imshow('avg',res)
            k = cv2.waitKey(5000 ...