digital signal processing dsp with python programming

The book "Advanced Programming in UNIX environments" comes with many small and exquisite programs. When I read this book, rewrite the code in the book according to your own understanding (most of them are on the copybook) to deepen your understanding (it's too difficult to read a book, huh, huh ). This example is successfully tested on ubuntu10.04. Program Description: In a multi-threaded program, set a flag for the waiting

Python Linux signal programming signals, pythonsignals1. Signal Introduction The Soft Interrupt signal (signal) is used to notify the process of an asynchronous event. Processes can call kill to send Soft Interrupt signals to eac

Send SignalKill the current terminal with the KILL command at the terminalRAs above, when using kill-sigcont 2563 , the terminal ignores the signalWhen using kill-sigabrt 2563 , the terminal exits. Need to re-enter user name password login.int Kill (__pid_t __pid, int __sig) : Sends a signal to the specified process . The first parameter is the process number to pass the signal, and the second parameter is

This article mainly introduced the Python Digital Image processing advanced morphology processing, now shares to everybody, also gives everybody to make a reference. Come and see it together. Morphological processing, in addition to the most basic expansion, corrosion, open

Python core programming: digital type, python core programming1. Introduction to numeric types The numeric types in Python include integer, long integer, Boolean, double-precision floating point, decimal floating point, and plural. These numeric types are all unchangeable.

1. Signal IntroductionA soft interrupt signal (signal, also referred to as a signal) is used to notify the process that an asynchronous event has occurred. Processes can send soft interrupt signals to each other through system call kill. The kernel can also send a signal to

One of VC Digital Image Processing programming lectures Origin and Application of Digital Image Processing CndgThe Research of Digital Image Processing Methods comes from two main appli

When it comes to digital image processing programming, perhaps most people will think of MATLAB, but MATLAB has its own shortcomings:1, not open source, the price is expensive2, the software capacity is large. Generally more than 3G, high version even up to 5G or more.3, can only do research, not easily converted into software.Therefore, we use the

if the written Python program is multithreaded or multi-process, it involves the issue of program security exit. one, multi-process program exitthe child process needs to be killed one after the other before exiting the main process, or it will cause the main process to exit (CTRL + C) After the child process does not exit and continue to run.?Ii. exit of multi-threadedYou need to set the thread's "Daemon" property to "True" (The default is "False") w

When it comes to digital image processing, perhaps most people will think of MATLAB, but MATLAB has its own shortcomings:1, not open source, the price is expensive2, the software capacity is large. Generally more than 3G, high version even up to 5G or more.3, can only do research, not easily converted into software.Therefore, we use the Python scripting language

Analysis of divmod digital processing functions in python, pythondivmod Divmod (a, B) Function Chinese description: The divmod (a, B) method returns a // B (Division) and the remainder of a to B. The returned result type is tuple. Parameters: A and B can be numbers (including plural numbers) Version: Complex numbers cannot be processed before python2.3. English d

This article mainly introduced the Python Digital image processing skeleton extraction and the watershed algorithm, now shares to everybody, also gives everybody to make a reference. Come and see it together. Skeleton extraction and watershed algorithm also belong to the morphological processing category, which are pl

=color.rgb2gray (Io.imread ('D:/pic/mor.png')) DST=sm.white_tophat (Img,sm.square (21)) Plt.figure ('morphology', Figsize= (8,8)) Plt.subplot (121) Plt.title ('Origin Image') plt.imshow (Img,plt.cm.gray) Plt.axis ('off') Plt.subplot (122) Plt.title ('Morphological Image') plt.imshow (Dst,plt.cm.gray) Plt.axis ('off')6. Black Hat (Black-tophat)Function:skimage.morphology. Black_tophat (image, selem=none)Selem represents a structural element used to set the shape and size of a local area.Subtracts

50Line_gap: The maximum gap between lines. Increase this value to merge broken lines. Default is 10Return:Lines: A list of lines, formatted as ((x0, y0), (x1, y0)), indicating the start and end points . Below, we use the canny operator to extract the edges and then detect which edges are straight lines?ImportSkimage.transform as StImportMatplotlib.pyplot as Plt fromSkimageImportdata,feature#use probabilistic Hough Transform.Image =Data.camera () edges= Feature.canny (image, sigma=2, low_thresho

='Nearest') Ax3.set_title ("Segmented") forAxinchAxes:ax.axis ('off') Fig.tight_layout () plt.show ()Watershed algorithms can also be combined with gradients to achieve image segmentation. A general gradient image has a higher pixel value at the edge and a lower pixel value elsewhere, ideally at the edge of the ridge. Therefore, we can find the ridge according to the gradient.Example 2: Gradient-based watershed image segmentationImportMatplotlib.pyplot as Plt fromSciPyImportNdimage as Ndi fromSk

picture, and is a grayscale imagePlt.axis ('off')#coordinate dimensions are not displayedplt.show ()#Display windowAnother way to write is to:ImportMatplotlib.pyplot as Plt fromSkimageImportdata,colorimg=data.immunohistochemistry () HSV=COLOR.RGB2HSV (img) FIG, axes= Plt.subplots (2, 2, figsize= (7, 6)) ax0, Ax1, ax2, Ax3=Axes.ravel () ax0.imshow (IMG) ax0.set_title ("Original Image") Ax1.imshow (hsv[:,:, 0], CMap=Plt.cm.gray) Ax1.set_title ("H") Ax2.imshow (hsv[:,:,1], cmap=Plt.cm.gray) Ax2.se

), Plt.title ('ROI') Plt.imshow (ROI), Plt.axis ('if') plt.show ()After plotting the picture with plot, move the mouse over the picture, and the coordinates of the current point appear in the lower-right corner, along with the pixel values.Three, geometric transformationThe Image class has resize (), rotate (), and Transpose () methods for geometric transformations.1. Zoom and rotate the imageDST = img.resize ((+,+# Clockwise angle representation2. Converting imagesDST == = Im.transpose (image.

coordinateY2,X2 represents the coordinates of the second control pointY3,X3 represents the third control point coordinateThe weight represents the weight of the middle control point and is used to control the curvature of the curve. from Import Draw,data Import Matplotlib.pyplot as pltimg=Data.chelsea () RR, CC=draw.bezier_curve (150,50,50,280,260,400,2) Draw.set_color (img,[rr,cc],[255, 0,0]) plt.imshow (Img,plt.cm.gray)6. Draw Hollow CircleAnd the previous circle is the same, but the front is