Download E-books Mastering OpenCV with Practical Computer Vision Projects PDF

November 21, 2016 | Engineering | By admin | 0 Comments

By Daniel Lélis Baggio, Khvedchenia Ievgen, Naureen Mahmood, Roy Shilkrot

This is the definitive complex instructional for OpenCV, designed for people with uncomplicated C++ abilities. the pc imaginative and prescient initiatives are divided into simply assimilated chapters with an emphasis on functional involvement for a neater studying curve.

Overview

  • Allows somebody with easy OpenCV adventure to speedily receive talents in lots of computing device imaginative and prescient issues, for examine or advertisement use
  • Each bankruptcy is a separate venture masking a working laptop or computer imaginative and prescient challenge, written by means of a certified with confirmed event on that topic.
  • All initiatives comprise a step by step educational and entire source-code, utilizing the C++ interface of OpenCV.

In Detail

Computer imaginative and prescient is quickly turning into an incredible know-how and is utilized in Mars robots, nationwide safety structures, automatic factories, driver-less vehicles, and clinical photograph research to new types of human-computer interplay. OpenCV is the commonest library for desktop imaginative and prescient, offering thousands of complicated and quick algorithms. however it has a steep studying curve and constrained in-depth tutorials.

Mastering OpenCV with functional machine imaginative and prescient initiatives is the ideal booklet for builders with simply easy OpenCV abilities who are looking to test functional machine imaginative and prescient tasks, in addition to the pro OpenCV specialists who are looking to upload extra machine imaginative and prescient themes to their ability set or achieve extra adventure with OpenCV's new C++ interface sooner than migrating from the C API to the C++ API.

Each bankruptcy is a separate venture together with the mandatory heritage wisdom, so try out all of them one-by-one or bounce immediately to the initiatives you are so much in.

Create operating prototypes from this e-book together with real-time cellular apps, Augmented truth, 3D form from video, or song faces & eyes, fluid wall utilizing Kinect, quantity plate acceptance and so on.

Mastering OpenCV with useful laptop imaginative and prescient initiatives can provide quick education in 9 computing device imaginative and prescient parts with necessary projects.

What you'll research from this book

  • Perform Face research together with basic Face & Eye & dermis Detection, Fisherfaces Face acceptance, 3D Head Orientation, advanced Facial characteristic Tracking.
  • Do quantity Plate Detection and Optical personality acceptance (OCR) utilizing synthetic Intelligence (AI) equipment together with SVMs and Neural Networks
  • Learn Augmented truth for laptop and iPhone or iPad utilizing uncomplicated man made markers or complicated markerless common images
  • Generate a 3D item version via relocating a undeniable 2nd digicam, utilizing 3D constitution from movement (SfM) digicam reprojection methods
  • Redesign machine real-time laptop imaginative and prescient purposes to more desirable Android & iOS cellular apps
  • Use easy snapshot clear out results together with caricature, comic strip, paint, and alien effects
  • Execute Human-Computer interplay with an XBox Kinect sensor utilizing the entire physique as a dynamic input

Approach

Each bankruptcy within the booklet is anyone venture and every undertaking is built with step by step directions, in actual fact defined code, and comprises the required screenshots.

Who this booklet is written for

You must have simple OpenCV and C/C++ programming event ahead of interpreting this e-book, because it is geared toward desktop technological know-how graduates, researchers, and laptop imaginative and prescient specialists widening their expertise.

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Y; rot_mat. at(0, 2) += ex; rot_mat. at(1, 2) += ey; // rework the face snapshot to the specified attitude & dimension & // place! additionally transparent the remodeled snapshot history to a // default gray. Mat warped = Mat(DESIRED_FACE_HEIGHT, DESIRED_FACE_WIDTH, CV_8U, Scalar(128)); warpAffine(gray, warped, rot_mat, warped. size()); Separate histogram equalization for left and correct facets In real-world stipulations, it's normal to have powerful lighting fixtures on one 1/2 the face and vulnerable lights at the different. This has a massive influence at the face attractiveness set of rules, because the left- and right-hand aspects of an identical face will look like very diverse humans. So we'll practice histogram equalization individually at the left and correct halves of the face, to have standardized brightness and distinction on either side of the face. If we easily utilized histogram equalization at the left part after which back at the correct part, we'd see a truly certain facet within the center as the usual brightness could be varied at the left and the best part, to be able to eliminate this aspect, we are going to practice the 2 histogram equalizations progressively from the left-or right-hand facet in the direction of the guts and combine it with a whole-face histogram equalization, in order that the a ways left-hand aspect will use the left histogram equalization, the some distance right-hand part will use the correct histogram equalization, and the heart will use a soft mixture of left or correct price and the whole-face equalized price. the next snapshot exhibits how the left-equalized, whole-equalized, and right-equalized photos are mixed jointly: to accomplish this, we'd like copies of the entire face equalized in addition to the left part equalized and the precise part equalized, that is performed as follows: int w = faceImg. cols; int h = faceImg. rows; Mat wholeFace; equalizeHist(faceImg, wholeFace); int midX = w/2; Mat leftSide = faceImg(Rect(0,0, midX,h)); Mat rightSide = faceImg(Rect(midX,0, w-midX,h)); equalizeHist(leftSide, leftSide); equalizeHist(rightSide, rightSide); Now we mix the 3 photos jointly. because the pictures are small, we will simply entry pixels without delay utilizing the picture. at(y,x) functionality no matter if it's gradual; so let's merge the 3 photos by means of without delay gaining access to pixels within the 3 enter photographs and output pictures, as follows: for (int y=0; y(y,x); } else if (x < w*2/4) { // Mid-left 25%: mix the left face & complete face. int lv = leftSide. at(y,x); int wv = wholeFace. at(y,x); // mix extra of the complete face because it strikes // extra correct alongside the face. glide f = (x - w*1/4) / (float)(w/4); v = cvRound((1. 0f - f) * lv + (f) * wv); } else if (x < w*3/4) { // Mid-right 25%: combination correct face & complete face. int rv = rightSide. at(y,x-midX); int wv = wholeFace. at(y,x); // mixture extra of the right-side face because it strikes // additional correct alongside the face. waft f = (x - w*2/4) / (float)(w/4); v = cvRound((1.

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