Extracting regions of interest from images

Welcome to the second post in this series where we talk about extracting regions of interest (ROI) from images using OpenCV and Python.

As a recap, in the first post of this series we went through the steps to extract balls and table edges from an image of a pool table. We used simple OpenCV functions like inRange, findContours, boundingRect, minAreaRect, **minEnclosingCircle, circle, HoughLines, line etc **to achieve our objective.

For beginners in OpenCV, I would recommend to go through that post in order to get familiar with the usage of the above functions.

In this post we will look at a somewhat more complex problem and explore some methods which we can use to obtain the desired results.

Our task today is to extract the desired segments from an image which contains a snapshot of a patients brain activity map. The extracted segments can then be used in numerous applications e.g. in a Machine Learning model which can diagnose any health anomalies.

So let us start by looking at the input image itself. It is a typical report generated by medical instruments used in the field of Neurological Science which use sensors to detect signals from a patients brain and display them as colored maps. Typically there are four maps, all of which depict a certain feature and are analyzed together for diagnosis (further details are out of current scope).

Our target image for this exercise containing the four brain maps (image source author)

From the above image, we want to extract only the regions corresponding to the four maps (head scans) leaving everything else out. So lets get going.

The first step is detecting the edges of the segments we want to extract. This is a multi step process as mentioned below:

1. Convert the RGB image to gray-scale using “cvtColor()”
2. Remove noise from the gray-scale image by applying a blurring function “GaussianBlur()”
3. Finally applying the “Canny()” function to the blurred image to obtain the edges

#opencv #python #image-processing #computer-vision

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Laravel 7/6 Image Validation

In this image validation in laravel 7/6, i will share with you how validate image and image file mime type like like jpeg, png, bmp, gif, svg, or webp before uploading image into database and server folder in laravel app.

https://www.tutsmake.com/image-validation-in-laravel/

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how to integrate CKEditor in Django

how to integrate CKEditor in Django

Welcome to my Blog, in this article we learn about how to integrate CKEditor in Django and inside this, we enable the image upload button to add an image in the blog from local. When I add a CKEditor first time in my project then it was very difficult for me but now I can easily implement it in my project so you can learn and implement CKEditor in your project easily.

how to integrate CKEditor in Django

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Laravel 7/6 Image Upload Example Tutorial

Laravel image upload example tutorial. Here, i will show you how to upload image in laravel 7/6 with preview and validation.

Before store image into db and folder, you can validate uploaded image by using laravel validation rules. as well as you can show preview of uploaded image in laravel.

Image Upload In Laravel 7/6 with Validation

Image upload in laravel 7/6 with preview and validation. And storage image into folder and MySQL database by using the below steps:

Install Laravel Fresh App
Setup Database Details
Generate Image Migration & Model
Create Image Upload Route
Create Image Controller
Create Image Upload and Preview Blade View
Start Development Server

https://www.tutsmake.com/laravel-7-6-image-upload-with-preview-validation-tutorial/

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Preprocessing your images for machine learning (image recognition)

During my studies at JKU there was a task for preprocessing images for a machine learning project. It is necessary to clean the raw images before using them in a learning algorithm, so thats why we create a pre-processing function. I think it can be quite useful for others as well so I want to share a bit of my approach. The file is structured in a way that it is easy to understand and also should have a tutorial-like effect.

#image-recognition #image #image-classification #machine-learning #image-processing

Crop and Resize Image Before Upload In Laravel Using with jQuery Copper JS

Crop and resize image size before upload in laravel using jquery copper js. In this post, i will show you how to crop and resize image size in laravel using jQuery copper js in laravel.

This laravel crop image before upload using cropper js looks like:

Laravel Crop Image Before Uploading using Cropper js Tutorial

Laravel crop image before upload tutorial, follow the following steps and learn how to use cropper js to crop image before uploading in laravel app:

• Step 1: Install New Laravel App
• Step 2: Add Database Details
• Step 3: Create Migration & Model
• Step 4: Add Route
• Step 5: Create Controller By Artisan
• Step 6: Create Blade View
• Step 7: Make Upload Directory
• Step 8: Start Development Server

Read More => https://www.tutsmake.com/laravel-crop-image-before-upload-using-jquery-copper-js/

Live Demo Laravel Crop image Before Upload.

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