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Questions tagged [image-segmentation]

Segmentation is a basic operation in image processing: its purpose is to group similar pixels into coherent regions = segments.

In image processing, image segmentation is the process of partitioning an image into multiple segments (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics.

The result of image segmentation is a set of segments that collectively cover the entire image. Each of the pixels in a region are similar with respect to some characteristic or computed property, such as color, intensity, or texture. Adjacent regions are significantly different with respect to the same characteristic(s).

Image segmentation is somewhat related to perceptual grouping: the spatial organization of visual stimuli. Some image segmentation algorithms attempt to employ Gestalt Laws of perceptual grouping to produce visually meaningful image segments.

Some popular image segmentation algorithms are Normalized cuts (by Shi and malik) and Mean-shift (by Comaniciu and Meer).

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Data Augmentation using ImageDataGenerator Keras

I am doing a Brain Segmentation project using the BRaTs2018 dataset where I'm feeding my network two arrays in each iteration: Input=(Batch_NR, Width, Height, NR_Channels) and Segmentation=(Batch_NR, Width, Height, NR_Classes). I am using the…
rodrigoappinto
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why am I getting a value greater than 1 as dice score

I have two segmented images, and I've computed the dice score using the formula below, however, I keep getting values greater than 1 (like 11.8, 12.8) as a dice score. is there a reason why? or is my approach for computing the dice score wrong? def…
a__ys
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Merging two custom Keras models into new model

I am trying to build a custom model that feeds the input to two pretrained Unet models which I defined in a separate file (without the Sequential class), locks their weights, concatenates their outputs, and finally end it with a 1x1 2D convolution…
Noam Suissa
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Segment image into sub-images components using python

I am working on medical images containing sub-images. I want to segment these image types into their component sub-images. I tried a lot of codes that do segmentation but nothing of segment the image into the sub-images parts. please help me to do…
Eda
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Split labelling image parts into sub labelled images using python

I am working on medical images. I want to segment each image into sub-segments parts according to the labelled letter in each part of the image. I have tried multiple codes and functions but I don't know how can I do that. Example of my dataset The…
Eda
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Image segmentation with UNet is mainly white

I'm working with MONAI library in order to segment brain tumor in MRI images. My dataset is composed of 500 patients and for each patient there're three types of images and the segmentation mask. I've trained my network (UNet architecture) but I've…
Alessandra Introvaia
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How can I download Bath 800 dataset?

how I can find valid link for download BATH800 dataset? "This dataset is a collection of eye images" I tried to find the download link through the references given in different articles. But these links have problems and do not work.
mohammad zeidi
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Image segmentation with a wide range of intensity values (Otsu thresholding)

I have raw microscopy images like this: And I want to segment the objects, as you see some of them are really close and I have a great range of intensity values. background: 700 a.u. fluorescent shapes: from 7000 to 32000 a.u. To segment them I use…
Claudia Salat
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Filter segments returned by felzenszwalb

I use felzenszwalb algorithm in skimage.segentation to do segmentation. However, some regions that contains 0 only has also been highlighted. from skimage.segmentation import felzenszwalb segments_fz = felzenszwalb(img) result = mark_boundaries(img,…
user16971617
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How to improve performance of cell segmentation using watershed algorithm with opencv-python

I have tried to segment cells in H&E-stained histopathological images using Watershed algorithm of opencv-python. The code I used is totally same as Docs opencv code in link below. Watershed Code Source But as you see the result, the performance of…
hailey
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OpenCV's GrabCut produces unsatisfactory segmentation

I have the following image I want to identify the main object in this image, which is the blue couch, and remove the background (preferably turn it into white). I use the code below, but it's not really doing the job as You can see in the second…
Parseval
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Branching points(OpenCV,C++)

I want to identify the branching points of the lightning in this image: https://i.stack.imgur.com/PXujf.jpg What I did first was threshold the image such that I get the lighning part of the image and discard the backround. This is the…
user854576
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Tensorflow lite model maker for react native

I am building a mobile app for scanning receipts from images. I collected enough datasets for the app and app is also almost completed. I tried with some tflite models which are free open sourced online but in my case of scanning receipts, it…
Kyle Moore
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Can I split a contour image in subregions?

I have an image with some contours: I want to segment the sections that appear around those contours, ideally based in the distance among the adjacent lines. As in the image below, I need to split it in subregions as the ones red and pink colored.…
Pedro
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Multi-Object Tracking from Segmentation Masks

Say I already have segmentation masks of some (biological) cells that I want to track; these cells are fairly similar to one another but do still vary slightly in shape and may also change shape as they are moving. Importantly, these cells do not…
Crazed
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