Increasing the probability of recognizing a target using a two-dimensional image from the sensor of the visible range of the onboard complex of information support for search and rescue operations in the Arctic

The article addresses the task of improving target recognition in onboard information support system for search and rescue operations in the Arctic region. One of the tasks performed by the complex is recognition of objects in twodimensional camera images, which suffer from the loss of the image brightness, being formed by constant brightness principle, with its direct impact on the probability of target recognition. To preserve the brightness of the image, the authors propose to process the primary signals of the camera according to the principle of constant color brightness. The proposed processing can increase the probability of correct target recognition. The paper analyzes the principles of encoding the primary signals of the television camera. For the object recognition problem, the cascades were trained based on the cascade classifier using the principles of constant brightness and constant color brightness. The output of the trained cascades has confirmed that the processing of the primary signals of a television camera based on the principle of constant brightness improves target recognition and therefore will increase the object recognition performance of the complex under development.

Prediction of the concentration of dye and nanosilver particle on silk fabric using artificial neural network

Purpose This study aimed to Simultaneous matching of color and antimicrobial properties of silk fabric treated with silver nanoparticle. The antimicrobial finishing using silver nanoparticles (AgNPs) is one of the most important finishing processes in the textile industry. Color matching is widely applied in the textile industry, but there has been a need for the prediction of AgNPs concentration for the matching of dyed silver-treated samples. Design/methodology/approach In this research, the silk fabrics were dyed with various concentrations of C.I. Acid Red 359 dye at 0.5, 1, 1.5 and 2 per cent (w/w). The dyed fabrics were then coated with AgNPs in several concentrations at 0.015, 0.030, 0.050, 0.100 and 0.250 ml/l. The prediction of dye and AgNPs concentrations were evaluated using single constant color matching and artificial neural network techniques. Findings The obtained results indicate that the accuracy of dye concentration prediction, as well as AgNPs concentration prediction, was improved by using a neural network method. Also, the correlation between actual and predicted dye and AgNPs concentrations in the best neural networks is more than the single constant color matching method. Originality/value Simultaneous antibacterial and color matching of nanosilver-treated fabric is novel. This method achieved acceptable accuracy for antibacterial and color matching.

Selective Attention in Inattentional Blindness: Selection is Specific but Suppression is Not

When we selectively attend to one set of objects and ignore another, we often fail to notice unexpected events. The likelihood of noticing varies depending on the similarity of an unexpected object to other items in the display, a process thought to be controlled by the attention set that we create for the attended and ignored objects. It remains unclear, though, how attention sets are formed and structured. Do they enhance features of attended objects (“white”) and suppress features of ignored objects (“black”), or do they distinguish objects based on relations or categories (“darker” versus “lighter,” or “dark objects” versus “light objects”)? In previous work, these explanations are confounded; the objects would be partitioned into the same groups regardless the structure of the attention set. In the present three experiments, the attended or ignored set of objects was a constant color while the other set was variable. When people attended white and ignored a multicolored set of objects (Experiment 1), novel colors were suppressed just as much as display colors, suggesting nonselective filtering of nonwhite objects. When the color of one set of objects varied across displays but was constant within them (Experiments 2 and 3), we again found as much suppression for task-irrelevant and novel colors as for actively ignored ones. Whenever people ignored a set of objects that varied in color, they suppressed unexpected objects that matched the ignored colors and that differed from the actively ignored items on the critical trial. In contrast, when people attended a varying set, noticing was enhanced only for unexpected objects that matched the currently attended color. In this task, attentional filtering is category-based and did not depend on the features of the individual objects.

The Control of Single-color and Multiple-color Visual Search by Attentional Templates in Working Memory and in Long-term Memory

The question whether target selection in visual search can be effectively controlled by simultaneous attentional templates for multiple features is still under dispute. We investigated whether multiple-color attentional guidance is possible when target colors remain constant and can thus be represented in long-term memory but not when they change frequently and have to be held in working memory. Participants searched for one, two, or three possible target colors that were specified by cue displays at the start of each trial. In constant-color blocks, the same colors remained task-relevant throughout. In variable-color blocks, target colors changed between trials. The contralateral delay activity (CDA) to cue displays increased in amplitude as a function of color memory load in variable-color blocks, which indicates that cued target colors were held in working memory. In constant-color blocks, the CDA was much smaller, suggesting that color representations were primarily stored in long-term memory. N2pc components to targets were measured as a marker of attentional target selection. Target N2pcs were attenuated and delayed during multiple-color search, demonstrating less efficient attentional deployment to color-defined target objects relative to single-color search. Importantly, these costs were the same in constant-color and variable-color blocks. These results demonstrate that attentional guidance by multiple-feature as compared with single-feature templates is less efficient both when target features remain constant and can be represented in long-term memory and when they change across trials and therefore have to be maintained in working memory.

Spectral Separation Method for Multi-Ink Printers Based on Color Constancy

Color constancy is a key metric for evaluating the color reproduction performance. This contribution proposed a color constancy based spectral separation method for muti-ink printers from the prospect of color perception. Basing on our previously developped spectral printer modeling workflow, a novel color constancy based spectral separation method for muti-ink printers was proposed, which achieved high-level color-constant color reproduction.The experiment results shows that the workflow described in the paper not only could makes full use of device gamut, but also improves the comprehensive color constancy performance obviously. Averagely speaking, the Color Inconstancy Index of reproduced colors is reduced from 2.884 △E00 to 2.016 △E00 , while maintaining reasonable spectral and colorimetric reproduction accuracy.