Color detection algorithm for early fire diagnostics

In the paper as a problem domain was chosen oil mining and its peculiarities related to early fire diagnostics. Main feature of the described method of early fire diagnostics is application of color detection algorithm together with video sequence acquired from survey cameras. Drawback of the known algorithms of fire diagnostics that also use video streams is selection of the only one color of visible spectrum. Proposed algorithm makes frames preprocessing with purpose of white noise and Gaussian noise suppression. Main feature is complex registration of color components of fire images that are specific to chosen problem domain. Described obtained results of practical application of proposed color detection approach. Experiments were carried out using test video sequences from Bilkent University and Dyntex database. It is shown that advantage of the proposed approach is an ability to select different color components and process them in complex during color detection.

Technologies for environmental monitoring of the city

IoT technologies in the Big Data concept can radically change approaches in agricultural practices, but it is necessary to work out methods of processing and interpreting information that can be effective in crop practice. Since the dimensions of plants are too small for satellite imagery, the development of technologies can be done on trees whose dimensions are sufficient for their identification in satellite imagery. The purpose of the work is to identify and assess the condition of plantations, in particular trees, with the determination of their positioning on satellite images of megacities. Digital photographs created by optical and infrared lenses of the Obolonskyi district of Kyiv were used for the research. It was found that in the optical range for objects under direct sunlight, plant identification is possible, while shaded areas are identified with significant errors. When using the index for IR shooting IRtree = C1 - C2 + 100 it was possible to identify individual ranges that belong to the crown of trees and grass in direct sunlight and to some extent in the shade, which could not be achieved with the index for optical range GBtree = G - B + 100. Monochrome infrared and optical images were not suitable for plant identification, because when objects were in the shadow of buildings, the ranges of intensity of the color components of plants were superimposed on the ranges of foreign objects. For infrared and optical satellite images, spectral indices have been proposed that take into account several color components to assess the condition of plantations. For tree crowns under direct sunlight, approximately the same results were obtained for the proposed indices. However, the indices proposed for infrared photography are more selective, as they were able to identify separately the crowns of trees and plants on lawns, both in direct sunlight and in the shade of buildings.

Image Hashing Algorithm Based on Mirror Flipping and a Three-Dimensional Space Angle

In order to make full use of image flipping information to get comprehensive image features and improve the distinguishing performance of hash algorithm, this paper proposes a new image hashing algorithm based on mirror flipping and a three-dimensional space angle. Firstly, the original image is preprocessed and then combined with mirror flipping image to obtain the new luminance component and opposite color components. Then, we combine new luminance component with the different sizes of structural elements to construct morphological features. The new opposite color components are used to construct a three-dimensional space. The angle between vectors formed by the pixels in the three-dimensional space is computed to construct the space angle features. Finally, the morphological features and space angle features are combined and disturbed to form the final hash sequence. Simulation results show that the algorithm has good security and tamper image recognition accuracy. Compared with some existing algorithms, it has better image classification performance and shorter computation time.

Chemical Modification Treatments on Extra-Long Egyptian Cotton Fiber

The efficiency of physical and chemical properties on Extra-long stable Egyptian cotton fiber Giza 96 at different treatment processes with two concentrations of morpholine comparing with conventional treatment with sodium hydroxide (NaOH) was investigated. The sample was pretreated with ferrous sulfate before dyeing with direct dye or natural dye. Physical properties as tensile strength (g/tex), elongation %, fiber length (UHM, and U.I), micronaire reading, reflectance (Rd %), and yellowness (+b) as well as chemical properties as crystallinity degree, moisture regain, accessibility, color strength (K/S), color components and color difference (?E) was also investigated. The results show that the chemical modified cotton fiber with sodium hydroxide (NaOH) were increased amorphous cellulose %, moisture regain %, accessibility %, fiber uniformity index (U.I) %, elongation %, and micronaire reading compared with morpholine treatments. On the other hand, tensile strength, and fiber length (U.H.M), decreased with a little degree values in morpholine treatments comparing with sodium hydroxide. Improvement in color strength (K/S), and color components was observed using morpholine instead of NaOH. These results were important for finishing textile production and textile industry.

Design and Realization of Animation Composition and Tone Space Conversion Algorithm

In recent years, with the development of society and the rapid development of the animation industry, people are paying more and more attention to and requirements for animation production. As an indispensable part of animation production, picture composition plays a major role in animation production. It can give full play to the application of color matching and light and shadow design and enhance the depth and space of the animation screen. Tone space conversion refers to the conversion or representation of color data in one color space into corresponding data in another color space. Its purpose is to distinguish and process color components such as hue and saturation in an image. This article first introduces the domestic and foreign research status of digital image preprocessing and analyzes the basic principles of several color space conversions in detail. Then, several color space conversion algorithms are studied, and the performance of the algorithms is compared and analyzed. The paper focuses on the hardware implementation and optimization of the algorithm for converting RGB color space into HSI color space to meet the real-time requirements. This article focuses on the mutual conversion between the RGB tone space and the HSI tone space and describes in detail how each color component in the HSI tone space is converted from the three RGB color components from a geometric perspective, and then the conversion is derived, and several general conversion methods of RGB to HSI tone space are introduced; two conversion methods of geometric derivation method and standard modulus algorithm are implemented in the software, and the comparison verification is carried out, and the comparison is made from the perspective of hardware implementation. The pros and cons of the two methods are discussed. Finally, the paper summarizes the shortcomings in the design and proposes further research directions in the future.

The Effect of the Addition of Fiber Preparations on the Color of Medium-Grounded Pasteurized and Sterilized Model Canned Meat Products

A beneficial aspect of the use of fiber preparations in the meat industry is the improvement of some quality characteristics of meat products. However, the preparation added in the amount of 3 or 6% may affect their color. The effect of the addition of barley, wheat and oat fiber preparations with different fiber lengths, in quantities allowing the product to be indicated as “high in fiber” or “source of fiber”, to pasteurized or sterilized medium-grounded canned meat products on their color, was determined. In the obtained canned meat products, the basic chemical composition and the L*, a* and b*, C* (Chroma) and h* (hue angle) color components were determined. The addition of the barley fiber preparation BG 300 to the model canned meat products caused a significant (p ≤ 0.05) darkening and an increase in the proportion of yellow color. In an industrial practice, this may result in poorer consumer acceptance of the meat product. Fiber length of wheat and barley fiber had no effect on the color components of products. The 6% addition of the wheat fiber preparations WF 200R and WF 600R or the oat fiber preparations HF 200 and HF 600 caused an apparent lightening of their color (ΔE > 2) compared to the control products.

Significance of Color Spaces & their Selection for Image Processing: A Survey

: The human visual system is encompassed with three components that help to produce a color sensation. The color display devices use this concept and create their full range of colors by incorporating all three primary color components. Any displayable color can be created with the help of these primaries. This paper comprises the concept of color space, which helps to understand a particular device’s color proficiencies. Since colors are a more robust descriptor, color spaces are considered to play a significant role in representing an image appropriately. The performance of many algorithms depends on the selection of an appropriate color space. There are many kinds of color spaces that can be used in real-time applications. These are RGB, nRGB, HSV, TSL, YCbCr, YUV, YES, CIE-XYZ, CMYK, etc. In this paper, color spaces and their vast classification are described in brief. Apart from these, the characteristics, applicability, limitations, mathematical conversion, and other essential factors are also explained for each color space.

Chemical separation of acrylic color components enabling the identification of the pigment spectroscopic response

Acrylic colors are mixtures of several components that can be identified as pigments, binders, and fillers, so that, when analyzed, the characteristic response of the different components may not be recognizable. This limits the accuracy of spectroscopic techniques, nonetheless particularly useful as they are noninvasive and can be applied in situ on real artworks. Here, a method is proposed to chemically separate and identify the different components of acrylic colors, in order to be able to study their spectroscopic response separately, in particular by ultraviolet–visible–near-infrared diffuse reflectance. The results clearly show that the chemical and analytical method developed here is fully reliable, with the advantage of clearly separating the response of the different components without any change of their chromatic/chemical properties. As a case study, the new method is applied here to original acrylic colors used by the Italian artist Ico Parisi, in view of building a spectra database.