<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[hustllx的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/hustllx</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; hustllx]]></copyright><item><title><![CDATA[爬虫笔记-使用python爬取豆瓣短评]]></title><link>https://blog.youkuaiyun.com/hustllx/article/details/78648366</link><guid>https://blog.youkuaiyun.com/hustllx/article/details/78648366</guid><author>hustllx</author><pubDate>Tue, 28 Nov 2017 09:45:05 +0800</pubDate><description><![CDATA[之前说明
# -*- encoding:utf-8 -*-

import requests
from bs4 import BeautifulSoup
import re
import random
import time

s = requests.session()

def get_ip_list(url, headers):
    web_data = requests.get(ur]]></description><category></category></item><item><title><![CDATA[图像处理之边界跟踪]]></title><link>https://blog.youkuaiyun.com/hustllx/article/details/78503324</link><guid>https://blog.youkuaiyun.com/hustllx/article/details/78503324</guid><author>hustllx</author><pubDate>Fri, 10 Nov 2017 21:00:36 +0800</pubDate><description><![CDATA[matlab函数：B=bwboundaries(img)；
使用栈实现代码：
close all;clear all;
img = imread('G:/bound.jpg');
img = rgb2gray(img);
img = im2bw(img);
img=im2bw(img);
B=bwboundaries(img);%库函数结果

[m,n]=size(img);
k=1;
fla]]></description><category></category></item><item><title><![CDATA[图像处理之区域标记]]></title><link>https://blog.youkuaiyun.com/hustllx/article/details/78502993</link><guid>https://blog.youkuaiyun.com/hustllx/article/details/78502993</guid><author>hustllx</author><pubDate>Fri, 10 Nov 2017 20:28:27 +0800</pubDate><description><![CDATA[对应matlab函数：bwlabel，L = bwlabel(BW,n)，其中BW为二值图像，而n有两种取值：4和8，分别对应4连通和8连通，默认是8连通；
1.使用栈来实现区域标记代码：
close all;clear all;clc;
I=imread('cameraman.tif');
s=im2bw(I);
L8=bwlabel(s,8);

[m n]=size(s);
tmp=ze]]></description><category></category></item><item><title><![CDATA[图像处理之直方图均衡化]]></title><link>https://blog.youkuaiyun.com/hustllx/article/details/78092209</link><guid>https://blog.youkuaiyun.com/hustllx/article/details/78092209</guid><author>hustllx</author><pubDate>Tue, 26 Sep 2017 10:09:31 +0800</pubDate><description><![CDATA[直方图均衡化：将原图像的直方图通过变换函数修正为均匀得 直方图，使得各灰度级具有相同的出现頻数，均衡化后的图像看起来就更清晰（提高对比度）。
matlab实现函数：histeq,详见：http://www.ilovematlab.cn/thread-1499-1-1.html；
具体实现步骤：
      首先计算图像中各个像素值的出现的概率，然后计算累计概率，最后根据累计概率来计算最后的梯]]></description><category></category></item><item><title><![CDATA[图像处理之旋转实现笔记]]></title><link>https://blog.youkuaiyun.com/hustllx/article/details/78091908</link><guid>https://blog.youkuaiyun.com/hustllx/article/details/78091908</guid><author>hustllx</author><pubDate>Tue, 26 Sep 2017 09:43:40 +0800</pubDate><description><![CDATA[matlab实现：
      使用函数imrotate，调用格式为：B = imrotate（A,angle）;B=imrotate(A,angle,method);B=imrotate(A,angle,method,bbox);
      其中，A：输入图像；angle：角度，正数表示逆时针；method：插值算法，有‘nearest’,'bilinear','bicubic'；bbox]]></description><category></category></item></channel></rss>