Automatic Document Image Binarization using Bayesian Optimization

Document image binarization is often a challenging task due to various forms of degradation. Although there exist several binarization techniques in literature, the binarized image is typically sensitive to control parameter settings of the employed technique. This paper presents an automatic document image binarization algorithm to segment the text from heavily degraded document images. The proposed technique uses a two band-pass filtering approach for background noise removal, and Bayesian optimization for automatic hyperparameter selection for optimal results. The effectiveness of the proposed binarization technique is empirically demonstrated on the Document Image Binarization Competition (DIBCO) and the Handwritten Document Image Binarization Competition (H-DIBCO) datasets

Review of Face Detection Systems Based Artificial Neural Networks Algorithms

Face detection is one of the most relevant applications of image processing and biometric systems. Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition. There is lack of literature surveys which give overview about the studies and researches related to the using of ANN in face detection. Therefore, this research includes a general review of face detection studies and systems which based on different ANN approaches and algorithms. The strengths and limitations of these literature studies and systems were included also.Comment: 16 pages, 12 figures, 1 table, IJMA Journa

A Learning Framework for Morphological Operators using Counter-Harmonic Mean

We present a novel framework for learning morphological operators using counter-harmonic mean. It combines concepts from morphology and convolutional neural networks. A thorough experimental validation analyzes basic morphological operators dilation and erosion, opening and closing, as well as the much more complex top-hat transform, for which we report a real-world application from the steel industry. Using online learning and stochastic gradient descent, our system learns both the structuring element and the composition of operators. It scales well to large datasets and online settings.Comment: Submitted to ISMM'1

Measurements, Models, Systems and Design

531 s.

Grounding semantics in robots for Visual Question Answering

In this thesis I describe an operational implementation of an object detection and description system that incorporates in an end-to-end Visual Question Answering system and evaluated it on two visual question answering datasets for compositional language and elementary visual reasoning

The ALHAMBRA Project: A large area multi medium-band optical and NIR photometric survey

(ABRIDGED) We describe the first results of the ALHAMBRA survey which provides cosmic tomography of the evolution of the contents of the Universe over most of Cosmic history. Our approach employs 20 contiguous, equal-width, medium-band filters covering from 3500 to 9700 A, plus the JHKs bands, to observe an area of 4 sqdeg on the sky. The optical photometric system has been designed to maximize the number of objects with accurate classification by SED and redshift, and to be sensitive to relatively faint emission lines. The observations are being carried out with the Calar Alto 3.5m telescope using the cameras LAICA and O-2000. The first data confirm that we are reaching the expected magnitude limits of AB<~25 mag in the optical filters from the blue to 8300 A, and from AB=24.7 to 23.4 for the redder ones. The limit in the NIR is (Vega) K_s~20, H~21, J~22. We expect to obtain accurate redshift values, Delta z/(1+z) <~ 0.03 for about 5x10^5 galaxies with I<~25 (60% complete), and z_med=0.74. This accuracy, together with the homogeneity of the selection function, will allow for the study of the redshift evolution of the large scale structure, the galaxy population and its evolution with redshift, the identification of clusters of galaxies, and many other studies, without the need for any further follow-up. It will also provide targets for detailed studies with 10m-class telescopes. Given its area, spectral coverage and its depth, apart from those main goals, the ALHAMBRA-Survey will also produce valuable data for galactic studies.Comment: Accepted to the Astronomical Journal. 43 pages, 18 figures. The images have been reduced in resolution to adapt to standard file sizes. Readers can find the full-resolution version of the paper at the ALHAMBRA web site (http://www.iaa.es/alhambra) under the "Publications" lin