LccSPM

本设计主要目的是实现染色体的识别计数。首先对图形进行预处理，将图像转化为灰度图、滤波去噪，然后对图像进行二值化，合理选取阈值，进行直方图阈值处理，最后去除图像中面积过小的杂点，最终实现识别计数。(The main purpose of this design is to achieve the identification of chromosome count. The graphical pre-processing, the image is converted to grayscale, filtering denoising, image binarization, reasonable selection of the threshold, histogram thresholding, and finally remove the image area is too small noise , and ultimately identify the count.)

实现对酒瓶子的边缘检测，背景差分，垂直和水平投影等，并可实现计数功能。(Achieve the bottles of edge detection, background difference, the vertical and horizontal projection, and to achieve counting.)

由VC实现画矩形、椭圆和随手画功能，对图像处理人员会有帮助(paintings by VC rectangular, oval and hand painting functions, image processing staff to be helpful)

这是一个很全的云模型图像处理，功能全，已运行(This is a good use of the cloud model program, function, good effect, has been in operation)

说明：  SDK_key: 人脸追踪(FT) Key 5qTrdeA43zdBXJZt7HM1x1wX9XGt7QicRU6Nt8rXLQAn 人脸检测(FD) Key 5qTrdeA43zdBXJZt7HM1x1weJvY2koYyzGARH6wVoTVw 人脸识别(FR) Key 5qTrdeA43zdBXJZt7HM1x1wmUKoEpvhgJYHd5xAsFig3 年龄识别(Age) Key 5qTrdeA43zdBXJZt7HM1x1xPHL78Ekcog6LU5iNCCNLj 性别识别(Gender) Key 5qTrdeA43zdBXJZt7HM1x1xWSjNHHcbTHHP9VuHLX1rf 此处APP_Id与SDK_Key仅适用于ArcFace v1.1， 不适用于其他版本。(DK_key: Face Tracking (FT) Key 5qTrdeA43zdBXJZt7HM1x1wX9XGt7QicRU6Nt8rXLQAn Face Detection (FD) Key 5qTrdeA43zdBXJZt7HM1x1weJvY2koYzGARH6wVoTVw Face Recognition (FR) Key 5qTrdeA43zdBXJZt7HM1x1wmUKoEpvhg JYHd5xAsFig3 Age Identification (Age) Key 5qTrde A43zdBXJZt7HM1x1xPHL78Ekcog 6LU5iNCCNLj Gender Key 5qTrdeA43zdBXJZt7HM1x1xWSjNHcbTHHP9VuHLX1rf Here APP_Id and SDK_Key are only applicable to ArcFace v1.1, not to other versions.)

用C语言实现的离散傅里叶变换（DFT）的经典算法！比较实用！(C language classic of the discrete Fourier transform (DFT) algorithm! More practical!)

说明：  模糊分割，基于混沌粒子群以及二维直方图的斜分阈值分割(Fuzzy partition, based on chaotic particle swarm and the oblique two-dimensional histogram thresholding)

使用ROEWA算子对有噪声SAR图像进行边缘检测(Use ROEWA operator of noise SAR image edge detection)

TV算法图像处理。total variation减少图像噪声算法源代码(TV algorithm for image processing. total variation image noise reduction algorithm source code)

采用分水岭算法对图像进行分割。直接对图像进行分水岭算法，效果并不理想。本方法使用形态学重建技术对前景对象进行标记，求局部极大值，最终将分割好的图像进行伪彩色显示，让结果更加明显。适用于较复杂的图像分割处理。(Using watershed algorithm for image segmentation. Watershed algorithm for image directly, the effect is not ideal. This method uses morphological reconstruction technique foreground object is marked, find local maxima, eventually dividing good pseudo-color image display, make the results more apparent. Applicable to more complex image segmentation processing.)