Image Segmentation at FcosAI

Updated: Jan 15, 2020

#ImageSegmentation #ImageProcessing #AI #DeepLearning #AIML

In computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as image objects). 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. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. 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 characteristics.

The result of image segmentation is a set of segments that collectively cover the entire image or a set of contours extracted from the image. Each of the pixels in a region is 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). When applied to a stack of images, typical in medical imaging, the resulting contours after image segmentation can be used to create 3D reconstructions with the help of interpolation algorithms like Marching cubes.

At FcosAI, we build an image segmentation tools which is completely automated and could be used to segment any type of image to identify the most visually prominent object in it.

We use a recent deep learning-based approach for the segmentation.

We provide API to integrate with your system for bulk segmentation. Below are a few example images that are segmented using our tools automatically.

From the above examples, you can see we build a class agnostic object segmentation model that generalizes well for any type of object. There are a lot of use cases of these tools. Any Individuals and Photographers could use this for removing background without any editing.

This segmentation tool could be used for creating your Marketing content.

For e-commerce, this is a great tool to create clean product taxonomy by removing the noisy background. These tools could also be used for generating segmentation data for your AI model.

If you are looking to scale up your image segmentation process, try FcosAI.

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