Object Tracking Using HSV Values and OpenCV

This research shows how to use colour and movement to automate the process of recognising and tracking things. Video tracking is a technique for detecting a moving object over a long distance using a camera. The main purpose of video tracking is to connect target objects in subsequent video frames. The connection may be particularly troublesome when things move faster than the frame rate. Using HSV colour space values and OpenCV in different video frames, this study proposes a way to track moving objects in real-time. We begin by calculating the HSV value of an item to be monitored, and then we track the object throughout the testing step. The items were shown to be tracked with 90 percent accuracy. Keywords: HSV, OpenCV, Object tracking, Video frames, GUI

The Geography of Words

Languages around the world organize their lexicons, or vocabularies, in a myriad of different ways. This book is a celebration of global linguistic diversity, bringing together fascinating cases from a wide range of languages to explore how and why this lexical variation occurs. Each of the thirty-six short chapters shows how different culturally-specific words, relating to a range of phenomena such as kinship, colour, space, time, objects, smells, and animals, vary across languages and geographical locations. It also explains the mechanisms of development in vocabularies, showing why this variation occurs, and how languages and cultures interact, to deepen the reader's understanding of one of the most important aspects of linguistics. Assuming little to no prior knowledge of linguistics, and introducing concepts in an accessible way, this book is an entertaining, informative read for anyone who wants to learn more about the incredible variation and diversity of the human lexicon.

Research on the Application of Artificial Intelligence Technology in Computer Graphics Processing

In structured light geometric reconstruction, due to the complexity of shooting methods and scene lighting conditions, the resulting images may be lack of image details due to uneven light. For this reason, the article proposes a Retinex algorithm with colour restoration and colour saturation correction strategy based on HSV colour space transformation based on artificial intelligence technology. Then distinguish whether it is a bright area according to the threshold value, and modify the insufficient transmittance estimation of the bright area. Finally, the intensity component and saturation value are restored in the HIS colour space, and the histogram is used to stretch the intensity component.

Double parton distributions out of bounds in colour space

We investigate the positivity of double parton distributions with a non-trivial dependence on the parton colour. It turns out that positivity is not preserved by leading-order evolution from lower to higher scales, in contrast to the case in which parton colour is summed over. We also study the positivity properties of the distributions at small distance between the two partons, where they can be computed in terms of perturbative splitting kernels and ordinary parton densities.

Individual Differences in Colour Perception: The Role of Low-Saturated and Complementary Colours in Ambiguous Images

Individual differences in colour perception, as evidenced by the popular debate of “The Dress” picture, have garnered additional interest with the popularisation of additional, similar photographs. We investigated which colorimetric characteristics were responsible for individual differences in colour perception. All objects of the controversial photographs are composed of two representative colours, which are low in saturation and are either complementary to each other or reminiscent of complementary colours. Due to these colorimetric characteristics, we suggest that one of the two complementary pixel clusters should be estimated as the illuminant hue depending on assumed brightness. Thus, people perceive the object's colours as being biased toward complementarily different colour directions and perceive different pixel clusters as chromatic and achromatic. Even though the distance between colours that people perceive differently is small in colour space, people perceive the object's colour as differently categorized colours in these ambiguous photographs, thereby causing debate. We suggest that people perceive the object's colours using different “modes of colour appearance” between surface-colour and self-luminous modes.

Optimising a Euclidean Colour Space Transform for Colour Order and Perceptual Uniformity

In this paper, we attempt to optimise a colour space transform for colour order and perceptual uniformity to verify if a trade-off could be achieved between the two. The IPT colour space is used as basis for the optimisation. An optimisation model consisting of a modified XYZ-to-LMS matrix, a nonlinearity factor, and two geometric transformation matrices is proposed. Two objective functions are constructed based on the optimisation model, where one would improve perceptual uniformity primarily and the other would improve colour order instead. Finally, the two objective functions are combined, in an attempt to optimise both simultaneously and see if a trade-off between the seemingly incompatible features can be achieved. The performance of the optimised IPT transform is then compared to the original IPT transform, in terms of relative improvements in perceptual uniformity and colour order. Finally, the results show that there is indeed an inverse relationship between the two objectives. However, by adjusting the bias of the optimisation, a balance could be achieved between the two, where both colour order and perceptual uniformity was improved with respect to the original IPT transform.

Major Flower Pigments Originate Different Colour Signals to Pollinators

Flower colour is mainly due to the presence and type of pigments. Pollinator preferences impose selection on flower colour that ultimately acts on flower pigments. Knowing how pollinators perceive flowers with different pigments becomes crucial for a comprehensive understanding of plant-pollinator communication and flower colour evolution. Based on colour space models, we studied whether main groups of pollinators, specifically hymenopterans, dipterans, lepidopterans and birds, differentially perceive flower colours generated by major pigment groups. We obtain reflectance data and conspicuousness to pollinators of flowers containing one of the pigment groups more frequent in flowers: chlorophylls, carotenoids and flavonoids. Flavonoids were subsequently classified in UV-absorbing flavonoids, aurones-chalcones and the anthocyanins cyanidin, pelargonidin, delphinidin, and malvidin derivatives. We found that flower colour loci of chlorophylls, carotenoids, UV-absorbing flavonoids, aurones-chalcones, and anthocyanins occupied different regions of the colour space models of these pollinators. The four groups of anthocyanins produced a unique cluster of colour loci. Interestingly, differences in colour conspicuousness among the pigment groups were almost similar in the bee, fly, butterfly, and bird visual space models. Aurones-chalcones showed the highest chromatic contrast values, carotenoids displayed intermediate values, and chlorophylls, UV-absorbing flavonoids and anthocyanins presented the lowest values. In the visual model of bees, flowers with UV-absorbing flavonoids (i.e., white flowers) generated the highest achromatic contrasts. Ours findings suggest that in spite of the almost omnipresence of floral anthocyanins in angiosperms, carotenoids and aurones-chalcones generates higher colour conspicuousness for main functional groups of pollinators.

Computer Vision Method for Forest Fires Detection Based on RGB Images Obtained by Unmanned Motor Glider

The article proposes a method (algorithm) of forest fire detection by means of RGB images obtained by using an unmanned aerial vehicle (motor glider). It includes several stages associated with background detection and subtraction and recognition of fire areas by means of RGB colour space. The proposed method was tested using images of forest fires. It is proposed to use unmanned aerial vehicles capable to monitor large areas continuously for several hours. The results of calculations are shown, which demonstrate that the proposed method allows us to detect areas of images occupied by forest fires and may be used in automatic forest fire monitoring systems.