This paper includes several new things aimed at matching microscopy images with small overlapping areas. However, we now use the same descriptor (FFF) for matching word images. The image below shows an image where two images of a kidney sample from a Mini-TEM microscopy are being matched. Even if the overlap is very small the … Continue reading Fast Fourier Features – and much more!
A Radial Line Integration Descriptor
This is the most simple feature descriptor I can imagine. It just samples and integrates along radial lines as shown in the figure below and the sum is stored as an element in the feature vector. Nonetheless, it works very well! This vector was the base for the RLF descriptor, which also includes sampling using … Continue reading A Radial Line Integration Descriptor
Mean-Max-Mean Features
This paper propose a very simple feature detector which computes the mean, max and min of pixels over columns and rows in a square mask. Then the squared difference of the mean and max, and the mean and min, respectively are computed (for each row and each column) and stored in a feature vector. This … Continue reading Mean-Max-Mean Features
Interactive Word Spotting
In this paper we propose to use visualisation of word spotting results as a powerful tool to be able to manually determine in an efficient manner which found words are correct and which are incorrect. This will make it possible to quickly make a reliable transcription of each word. An Intelligent User Interface for Efficient … Continue reading Interactive Word Spotting
Semi-Automatic Transcription
Word spotting can be used to make a semi-automatic transcription of the text. The idea is that the user should mark up the word that needs to be transcribed and then the word spotter finds all occurrences of that word. Hence, the word needs to be transcribed only once, and the process can be performed in … Continue reading Semi-Automatic Transcription
Anders Hast 