Component

We propose to use a kernel density estimation (KDE) based approach for classification. This non-parametric approach intrinsically provides the likelihood of membership for each class in a principled manner. The implementation was used in Ghani2016. Any papers using this code should cite Ghani2016 accordingly. The software has been tested under Matlab R2013b.

Sample Data: Annotated two-photon images of dendritic spines

This is a Matlab implementation of Local Phase Quantization (LPQ) texture descriptors that is robust to image blurring due to the use of phase information. Theoretical background could be found here: http://www.ee.oulu.fi/research/mvmp/mvg/files/pdf/ICISP08.pdf

This is a software toolbox that extends the original BSIF code allowing the utilization of a GPU in Matlab to compute the features. It contains: -Matlab function to calculate BSIF in CPU -Matlab function extension to calculate BSIF in GPU -Pre-learnt filters -Usage instructions

This is a Java content-based image retrieval software components. It can be runned independantly or connected to a Cytomine server. Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. Content-based" means that the search algorithm analyzes the contents of the image rather than the metadata such as keywords, tags, or descriptions associated with the image. The term "content" in this context might refer to colors, shapes, textures, or any other information that can be derived from the image itself. The CBIRetrieval library is: Incremental: You can add new images all over the time. Scalable: Run as many server as you want. Client performs search on all servers. Flexible: Run as a simple app (command line) or use the JAR in your own JVM app/server (java import) Opensource/Free: Apache 2.0 CBIRetrieval is a java library for CBIR, CBIRest is a server with a REST HTTP API with CBIRetrieval embedded. If you want to connect a software/webapp with a CBIR engine, you should use CBIRest. This is a fast multi-threaded and noSQL implementation of the algorithm published in: Incremental Indexing and Distributed Image Search using Shared Randomized Vocabularies Marée, Raphaël; Denis, Philippe; Wehenkel, Louis; Geurts, Pierre,in ACM Proceedings MIR 2010 (2010, March). It was applied on histology images and radiology images.

Matlab implementation (2014) of Local Binary Pattern. Used for texture image analysis with insensitivity to local average value. Good explanation here: http://www.ee.oulu.fi/research/imag/mvg/files/pdf/ICCV2009_tutorial.pdf