Search Results for "k-stor"

Sombrero is a fast wavelet image processing and object detection C library for astronomical images. Sombrero is named after the "Mexican Hat" shape of the wavelet masks used in image convolution and is released under the GNU LGPL library.

Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model. ACM Transactions on Graphics (presented at SIGGRAPH 2018) Exposure is originally designed for RAW photos, which assumes 12+ bit color depth and linear "RGB" color space (or whatever we get after demosaicing). jpg and png images typically have only 8-bit color depth (except 16-bit pngs) and the lack of information (dynamic range/activation resolution) may...

...The text extraction is achieved by a combination of statistical and graphical processing operations. It is based on the following 3 major algorithms - Binarization of color images (Niblak and other methods) - Connected components - K-Means clustering Apache Tesseract is used to perform Optical Character Recognition on the extracted text. A subsequent version of the application will integrate with translation software in order to provide automated translation of comic book texts and re-inserion of translated texts

Software collection for zebrafish image processing (under construction), including an Excel table for related tools and method papers, see also survey paper: Mikut, R.; Dickmeis, T.; Driever, W.; Geurts, P.; Hamprecht, F.; Kausler, B. X.; Ledesma-Carbayo, M. J.; Marée, R.; Mikula, K.; Pantazis, P.; Ronneberger, O.; Santos, A.; Stotzka, R.; Strähle, U. & Peyriéras, N. Automated Processing of Zebrafish Imaging Data - A Survey Zebrafish, 2013

...In particular, it allows the user to measure the volume of all distinguishable features in an image and to isolate and sort those particles. As the name implies, LAVA uses Lloyd's Algorithm, also known as k-means sorting, to identify a small set of volumes representative of the actual distribution of particle in the image. Although developed for determining feature volume, LAVA is also completely compatible with other types of image analysis, such as fluorescence intensity. Work is in progress to provide three-channel functionality, allowing comparison of relative intensity of red, green, and blue channels in multi-color images.