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表單驗證 調用為 onBlur=checkform(fname1,fname2,types,value1,value2) 輸入框的驗證 onSubmit subt(this.id) 表單提交時的驗證 兩者需要一起使用 fname1=驗證的項目名 fname2=驗證的副項目名 types=驗證的方式 value1=驗證的值1 value2=驗證的值2 驗證的方式值:(多驗證方式用"|"分割 例: 1|2|3) 0.該值不能為空! 1.您輸入太短了!不能小於value1字符 2.您輸入太多了!不能超過value2字符! 3.你的兩次密碼不一至,請驗證! 4.您的輸入與要求不相符,該輸入只能在value1~value2之間! 5.您輸入的E_mail不正確!請重新輸入! 6.只能為數字 */(calling for the certification form onBlur = checkform (fname1. fname2, types, value1, value2) input box test onSubmit subt (this.id) at the time of submission of the form Taken together need to verify the use of the test fname1 = fname2 = projects were validated by the deputy project were typ es = verifiable means value1 = the value of a certification value2 = 2 certification test the value of values : (multi-authentication "|" segmentation cases : 1 | 2 | 3) 0. The value can not be empty! 1. Your input is too short! value1 not less than two characters. You lose into too many! not more than value2 characters! 3. your password twice to different, Please validation! 4. Your input is not in line with requirements, The importation of only between value1- value2! 5. E_mail you enter )

实现了车辆目标的背景建模、前景检测、阴影消除、车辆跟踪(Achieve a vehicle target background modeling, foreground detection, shadow elimination, vehicle tracking)

python写的图像相似度算法。比较图像相似度，选出最相思的图片(python write the image similarity algorithm. Compare image similarity, image to select the most Acacia)

说明：  MATLAB实现基于互相关的亚像素级图像配准源代码,MATLAB_Image_subpixel_Mutual_info(MATLAB-based cross-correlation of sub-pixel image registration source code, MATLAB_Image_subpixel_Mutual_info)

SSR算法，自己已经测试过了，绝对可以使用！！！！而且我自己增加了直方图显示。希望能帮助到大家~~(SSR )

使用K-means聚类算法的改进算法K-means++对图像区域进行分割。(using the improved algorithm K-means++ segment image.)

KALMAN filtering algorithm under the matlab toolbox, Shared by everybody, good source is very good

对于图像不同纹理特征值（能量、熵、惯性矩、相关）的提取(For different image texture feature value (energy, entropy, moment of inertia, related) extraction)

基于模糊C-均值聚类算法的图像分割，消除二值分割的非此即彼的缺陷(Image segmentation based on fuzzy C- means clustering algorithm eliminates the defects of two value segmentation.)

OMP算法的matlab的详细描述，对学习正交匹配追踪算法和稀疏分解是很有用的(the OMP algorithm is describled by matlab,and it is very useful for us to study OMP algorithm and sparse decomposition.)