object-recognition

问题 Every implementation of SURF I have come across on the web seems to be particularly bad at extracting a useful number of interest points from small images (say, 100x100 or less). I have tried a number of approaches: 1) Using various upscaling algorithms (from simple one like nearest-neighbor to more advanced ones - basically every upscaler imagemagick provides) to increase the size of small images before analysis. 2) Other image processing tweaks to bring out features in the image such as

问题 To all skimage and opencv gurus, given: Scene Image Template Image What is the best approach to find the cross in the scene image ? These are output from smoothing, and canny filters. Now, I tried all kinds of examples in skimage, and opencv template matching but the results are not satisfactory. My ideal solution will be rotation, translation invariant (scale invariant will be a bonus) . Is there a way to just convert to contour points and them do a registration point cloud ? Will that be

问题 I have created a console application. Added a reference to tessnet2_32. Ocr ocr = new Ocr(); using (Bitmap bmp = new Bitmap(filename)) { tessnet2.Tesseract tessocr = new tessnet2.Tesseract(); tessocr.Init(@"C:\temp\tessdata", "eng", false); ... I also tried changing "C:\temp\tessdata" to C:\work\ConsoleApplication3\ConsoleApplication3 C:\work\ConsoleApplication3\ConsoleApplication3\tessdata C:\work\ConsoleApplication3\ConsoleApplication3\bin\debug C:\work\ConsoleApplication3

问题 I think this question is asked before but i didnt find a sample or solution for my problem. I am new to opencv and i want to use the OpenCV CameraPreview for paper sheet detection. In my sample app i use opencv 3.0.0 with static initialization. I understand that object recognition can done with these steps: Make the input image Canny Blur the Canny Image Find Contours on the blurred Canny Image Search for rectangles etc Draw lines or fill the rectangle with half transparent color My problem

问题 I am using Tensorflow Object Detection API to train my own object detector. I downloaded the faster_rcnn_inception_v2_coco_2018_01_28 from the model zoo (here), and made my own dataset (train.record (~221Mo), test.record and the label map) to fine tune it. But when I run it : python train.py --logtostderr --pipeline_config_path=/home/username/Documents/Object_Detection/training/faster_rcnn_inception_v2_coco_2018_01_28/pipeline.config --train_dir=/home/username/Documents/Object_Detection

问题 Problem Statement & Background Info: EDIT : Constraints: The red coloring on the flange changes over time, so I'm not trying to use color recognition to identify my object at this moment unless it can be robust. Addition,ally external illumination my be a factor since this will be in an outdoor area in the future. I have RGB-Depth camera and with it, I'm able to capture this scene. Where each pixel (x,y) has a depth value. Applying a gradient magnitude filter to the depth map associated with

问题 I'm trying to develop an AR android application. it should detect and recognize the object captured by the camera, I'm using OpenCV for this purpose, but I'm not very familiar with object recognition for mobile devices in the AR field. I have two questions: 1- which algorithm is better (in the meaning of precision and speed) SIFT, SURF, FAST, ORB, or something else? 2- I wonder if the process of detecting and tracking would be something like this : taking a camera frame, detect its key points

问题 I would like to develop, for academic purpouse, an object recognition system that uses (among other things) edges or corners matching. Basically I extract corner information on my model image then i try to find this object inside a query image using corner information. Do you have any hint within OpenCV? Ps. I know I could use SIFT/SURF/ORB but in this case i need to match corner or edges 回答1: What about Hough transform (contour matching)? Look at matchShapes function. 来源： https:/

问题 It's difficult to tell what is being asked here. This question is ambiguous, vague, incomplete, overly broad, or rhetorical and cannot be reasonably answered in its current form. For help clarifying this question so that it can be reopened, visit the help center. Closed 8 years ago . Have you any idea about implementing 2D object recognition with MATLAB? Which characteristics of objects can feed a neural network? 回答1: Object Recognition is generally one of the main part of all image

问题 Hello friend I want to recognize and determine the type of object into photo jpg or png with php, for example determine if exists a apple or grapes, or car, or animals into any photo. Please if somebody know about that, because I want to make exactly that. Regards Gildus 回答1: Object recognition in computer vision is an open and ongoing area of research. There's some good work being done, but we're a long way from being able to extract details about what's in a scene with ease. The Wikipedia