.NET news » Search results

Following on last month’s discussion of media queries, Brandon Satrom looks at the other two pillars of responsive Web design—fluid grids and flexible images. Media Queries are the engines that drive responsive, adaptive sites, but they are only effective when the designs of those sites are also responsive and adaptive. This month, I'll introduce you to some ideas around the other two pillars of "Responsive Web Design." I'll start with an overview of some up-and-coming CSS Layout modules, and then talk about some techniques for making non-textual elements like images and embedded video adaptive as well.

Process webcam images on the GPU with OpenCV and CUDA

The demo application is a Silverlight YouTube Jukebox which allows users to select artists, view their albums, select an album, and view the album's tracks. Users can right click on any track name and select to view the track details. By selecting a track (left click), users initiate a search for a YouTube video. Up to four possible matches are presented to the user as thumb images; the video title appears as the user mouses over the image. The user can then click on any of the images to view the YouTube video.

We've offered a few solutions for working with web cams within .NET to create fun and intriguing monitoring applications. In this article, we extend those ideas so that web cam images can be shared with multiple clients over the Web.

In addition to text recognition and similar capabilities, Ink can also be useful for image annotation and markup, such as in medical and insurance applications, where marking up images can be a valuable and critical form of input.

Localize text, images, and any other WPF property using standard RESX files

A program to produce beautiful and informative images of complex functions.

A library to extract EXIF information from images, compliant with Exif 2.2 standard

This code performs a fuzzy C-means clustering and segmentation of color images, can be used for feature extraction.

This article describes how to recognize playing cards from still images or from real-time webcam feeds ,using the AForge.NET framework(C#).