Deciphering Egyptian Hieroglyphs: Towards a New Strategy for Navigation in Museums

This work presents a novel strategy to decipher fragments of Egyptian cartouches identifying the hieroglyphs of which they are composed. A cartouche is a drawing, usually inside an oval, that encloses a group of hieroglyphs representing the name of a monarch. Aiming to identify these drawings, the proposed method is based on several techniques frequently used in computer vision and consists of three main stages: first, a picture of the cartouche is taken as input and its contour is localized. In the second stage, each hieroglyph is individually extracted and identified. Finally, the cartouche is interpreted: the sequence of the hieroglyphs is established according to a previously generated benchmark. This sequence corresponds to the name of the king. Although this method was initially conceived to deal with both high and low relief writing in stone, it can be also applied to painted hieroglyphs. This approach is not affected by variable lighting conditions, or the intensity and the completeness of the objects. This proposal has been tested on images obtained from the Abydos King List and other Egyptian monuments and archaeological excavations. The promising results give new possibilities to recognize hieroglyphs, opening a new way to decipher longer texts and inscriptions, being particularly useful in museums and Egyptian environments. Additionally, devices used for acquiring visual information from cartouches (i.e., smartphones), can be part of a navigation system for museums where users are located in indoor environments by means of the combination of WiFi Positioning Systems (WPS) and depth cameras, as unveiled at the end of the document.

A novel approach for weed type classification based on shape descriptors and a fuzzy decision-making method

An important objective in weed management is the discrimination between grasses (monocots) and broad-leaved weeds (dicots), because these two weed groups can be appropriately controlled by specific herbicides. In fact, efficiency is higher if selective treatment is performed for each type of infestation instead of using a broadcast herbicide on the whole surface. This work proposes a strategy where weeds are characterised by a set of shape descriptors (the seven Hu moments and six geometric shape descriptors). Weeds appear in outdoor field images which display real situations obtained from a RGB camera. Thus, images present a mixture of both weed species under varying conditions of lighting. In the presented approach, four decision-making methods were adapted to use the best shape descriptors as attributes and a choice was taken. This proposal establishes a novel methodology with a high success rate in weed species discrimination.

A stereovision matching strategy for images captured with fish-eye lenses in forest environments

We present a novel strategy for computing disparity maps from hemispherical stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. This is achieved by applying a pattern recognition strategy based on the combination of two classifiers: Fuzzy Clustering and Bayesian. At a second stage, a stereovision matching process is performed based on the application of four stereovision matching constraints: epipolar, similarity, uniqueness and smoothness. The epipolar constraint guides the process. The similarity and uniqueness are mapped through a decision making strategy based on a weighted fuzzy similarity approach, obtaining a disparity map. This map is later filtered through the Hopfield Neural Network framework by considering the smoothness constraint. The combination of the segmentation and stereovision matching approaches makes the main contribution. The method is compared against the usage of simple features and combined similarity matching strategies.

[Gm and Km allotypes in a Chilean urban population sample]

BACKGROUND

The knowledge of the genic structure of a population is of great importance for evolutive studies.

AIM

To estimate in a Chilean population sample from the low-middle and low socioeconomic strata of Santiago, haplotypes and allele frequencies for Gm and Km loci.

SUBJECTS AND METHODS

The sample included 460 controls of a case-control study of typhoid fever.

RESULTS

The G1m-G2m-G3m most frequent haplotypes were: za;..;g or 1,17;(-);21 = 0.4493;fn;b or 3;23;5,13 = 0.2522; f-,..;b or 3;(-);5,13 = 0.1389; zax;..;g or 1,2,17;(-);21 = 0.0685; za;..;b or 1,17;(-);5,13 = 0.0454; za;n;g or 1,17;23;21 = 0.0207; f;..;g or 3;(-);21 = 0.0129. The frequencies of Km alleles were 0.2391 and 0.7609 for Km1 and Km3 respectively.

CONCLUSIONS

These frequencies are within those found in Amerindian and Caucasian populations as expected from the origin of the Chilean population. Gm haplotypes did not differ from Hardy-Weinberg equilibrium, while a significant lack of homozygous Km1/km1 was found in Km.