image-segmentation | 易学教程

Extract hand bones from X-ray image

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问题 I have x-ray image of a hand. I need to extract bones automatically. I can easily segmentate a hand using different techniques. But I need to get bones and using those techniques don't help. Some of the bones are brighter then orthers, so if I use thresholding some of them disapear while others become clearer rising threshold. And I think maybe I should threshold a region of the hand only? Is it possible to threshold ROI that is not a square? O maybe you have any other solutions, advices?

Filling holes in objects that touch the border of an image

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I'm trying to fill holes in the below image. When I use SciPy's binary_fill_holes(), I am generally successful, with the exception of objects that touch the image's border. Are there any existing Python functions that can fill holes in objects that touch the border? I tried adding a white border around the image, but that just resulted in the entire image being filled. This assumes that there is more background than other stuff. It basically does a connected component analysis on the image. Extract the largest component (assumed to be the background), and sets everything else to white. import

Implementing skip connections in keras

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问题 I am implementing ApesNet in keras. It has an ApesBlock that has skip connections. How do I add this to a sequential model in keras? The ApesBlock has two parallel layers that merge at the end by element-wise addition. 回答1: The easy answer is don't use a sequential model for this, use the functional API instead, implementing skip connections (also called residual connections) are then very easy, as shown in this example from the functional API guide: from keras.layers import merge,

Image Processing - Dress Segmentation using opencv

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问题 I am working on dress feature identification using opencv. As a first step, I need to segment t-shirt by removing face and hands from the image. Any suggestion is appreciated. 回答1: I suggest the following approach: Use Adrian Rosebrock's skin detection algorithm for detecting the skin (thank you for Rosa Gronchi for his comment). Use region growing algorithm on the variance map. The initial seed can be calculated by using stage 1(see the attached code for more information). code: %stage 1:

Detection of leaf on unpredictable background

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A project I have been working about for some time is a unsupervised leaf segmentation. The leaves are captured on a white or colored paper, and some of them has shadows. I want to be able to threshold the leaf and also remove the shadow (while reserving the leaf's details); however I cannot use fixed threshold values due to diseases changing the color of the leaf. Then, I begin to research and find out a proposal by Horprasert et. al. (1999) in "A Statistical Approach for Real-time Robust Background Subtraction and Shadow Detection", which compare areas in the image with colour of the now

Segment an image using python and PIL to calculate centroid and rotations of multiple rectangular objects

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问题 I am using python and PIL to find the centroid and rotation of various rectangles (and squares) in a 640x480 image, similar to this one So far my code works for a single rectangle in an image. import Image, math def find_centroid(im): width, height = im.size XX, YY, count = 0, 0, 0 for x in xrange(0, width, 1): for y in xrange(0, height, 1): if im.getpixel((x, y)) == 0: XX += x YY += y count += 1 return XX/count, YY/count #Top Left Vertex def find_vertex1(im): width, height = im.size for y in

Image segmentation with maxflow

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问题 I have to do a foreground/background segmentation using maxflow algorithm in C++. (http://wiki.icub.org/iCub/contrib/dox/html/poeticon_2src_2objSeg_2src_2maxflow-v3_802_2maxflow_8cpp_source.html). I get an array of pixels from a png file according to their RBG but what are the next steps. How could I use this algorithm for my problem? 回答1: I recognize that source very well. That's the Boykov-Kolmogorov Graph Cuts library. What I would recommend you do first is read their paper. Graph Cuts is

Spectral Clustering, Image Segmentation and Eigenvectors

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Based on the book Computer Vision a Modern Approach page 425, I attempted to use eigenvectors for image segmentation. http://dl.dropbox.com/u/1570604/tmp/comp-vis-modern-segment.pdf The author mentions that image pixel affinites can be captured in matrix A. Then we can maximize w^T A w product where w's are weights. After some algebra one obtains Aw = \lambda w, finding w is like finding eigenvectors. Then finding the best cluster is finding the eigenvalue with largest eigenvector, the values inside that eigenvector are cluster membership values. I wrote this code import matplotlib.pyplot as

Image segmentation - Split and Merge (Quadtrees)

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Is there an implementation for the split and merge method of image segmentation? any advice would be much appreciated. What segmentation is about? Segmentation means division of your image into several connected regions. Basically, you could do segmentation with two definitions of region: you could define a region as a group of connected similar pixels, or a set of connected pixels surrounded by discontinuities (edges). Split and merge uses the first approach. Mathematically speaking: if your whole image is represented by the set of pixels (called R), than you would like to get subsets such as

Extract hand bones from X-ray image

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I have x-ray image of a hand. I need to extract bones automatically. I can easily segmentate a hand using different techniques. But I need to get bones and using those techniques don't help. Some of the bones are brighter then orthers, so if I use thresholding some of them disapear while others become clearer rising threshold. And I think maybe I should threshold a region of the hand only? Is it possible to threshold ROI that is not a square? O maybe you have any other solutions, advices? Maybe there are some libraries like OpenCV or something for that? Any help would be very great! Extended: