scholarly journals Automatic detection of petiole border in plant leaves

2020 ◽  
pp. 002029402091770
Author(s):  
Abdullah Elen ◽  
Emre Avuçlu

Plants are our source of oxygen and nutrients on earth. Therefore, conservation of biodiversity is vital for the survival of other species. With the developing technology, plant species can be examined more closely. Image processing, which is a subject of computer science, has an important role in this field. In this study, an image processing–based method has been developed to automatically separate the petiole region of the plant leaves. To determine the boundary line of the petiole region, the cumulative pixel distributions of the input images in binary format according to the X- and Y-axis are analyzed. Accordingly, optimum thresholds and petiole boundary points are determined. The proposed method was tested on 795 leaf images from 90 different plant species that grow both as trees and shrubs in the Czech Republic. According to the results obtained in experimental studies, it is thought that the proposed method will make an important contribution especially in studies such as automatic classification of plants and leaves and determination of plant species in botanical science.

Akustika ◽  
2021 ◽  
pp. 210-216
Author(s):  
Nickolay Ivanov ◽  
Aleksandr Shashurin ◽  
Aleksandr Burakov

The features of noise generation processes in exhaust and suction noise silencers are shown. A method for testing silencers has been developed. The classification of the main structural elements of exhaust and suction noise silencers, depending on the purpose, is proposed. Experimental studies of the relationship between the acoustic efficiency and the back pressure of silencers from the structural design of the elements are performed. The factors influencing the efficiency in the low-frequency and high-frequency regions of the spectrum are determined: the volume of silencers, the number of chambers, perforation, sound absorption, flow ejection, etc. Recommendations for the design of noise silencers are proposed.


2021 ◽  
pp. 82-91
Author(s):  
O. Tkachuk ◽  
S. Pankova

The aim is to analyze the resistance of tree and shrub vegetation used to create protective forest belts to air pollution on the basis of experimental studies conducted by other scientists. The research was carried out on the basis of the development of experimental materials on the resistance of tree and shrub vegetation to atmospheric pollution by dust and gases, presented in the works of famous scientists. The obtained results were generalized, the probability of growing gas- and dust-resistant trees in the conditions of climate change in relation to their drought resistance was estimated and the most resistant species of trees and shrubs were recommended. Also identified species of plants that can act as bioindicators of air pollution. Studied by Prysedsky Yu.G. (2014) plant species in terms of resistance to atmospheric pollutants with sulfur, nitrogen and fluorine compounds were divided into four groups: tolerant (resistant), moderately damaged, unstable and with variable resistance. The group of resistant species includes prickly pear, common oak, Tatar honeysuckle and caragana arborescens. These species can be used to create protective forest belts. At the same time, reliable plant indicators of sulfur, nitrogen and fluoride oxides in the air will be unstable plant species — mountain ash and poplar Bolle. Classification of trees and shrubs in terms of their resistance to atmospheric smoke divides plants into three groups: stable, relatively stable, unstable, with the allocation of primary and secondary wood species for forest belts, as well as shrubs. The most resistant to atmospheric smoke are white acacia, elm, white willow, forest pear, poplar, hazel, juniper, forest apple. They can be the main components of protective forest belts in the area of atmospheric smoke. Unstable species — red oak, Scots pine, horse chestnut, viburnum — are bioindicators of atmospheric smoke. There is also a classification of tree species by dust retention M.I. Kalinin (1991). Behind it the most dust of 1 m2 of leaves is retained by white mulberry — 8.1 g, weeping willow — 8.1 g, three-pricked  gladiolus — 5.1 g, elm — 4.1 g and field maple — 3.6 g. One tree absorbs the most dust during the growing season in weeping willow — 37.9 kg, Canadian poplar — 34.1 kg, white mulberry — 31.3 kg, ash — 27.1–29.6 kg, maple — 29,2 kg and high island — 24.2 kg. According to Vergeles (2000), poplars have the highest average relative dust resistance — 180 points, common ash — 170, bitter horse chestnut and linden leaf heart — 100 points each.


One of major issue nowadays is the agricultural productivity which is something our Nation’s economy highly depends. Technology based advancements may lead to detection of diseases in plants which are quite natural. Care should be taken in this area before it causes serious effects on plants which mainly affect the product quality, quantity or productivity. Early stage detection of diseases in plants through some automatic technique is beneficial as it reduces a huge work of monitoring in large acres of crops. When they appear on plant leaves, earlier detection helps us to increase the yield and productivity. This paper presents an algorithm for image processing technique which is used for automatic detection and classification of plant leaf diseases with the help of raspberry pi and sensors. This survey is about different diseases and its classification, techniques which are used for plant leaf disease detection and also its respective fertilizer sprayed on the leaves.


Author(s):  
B. Roy Frieden

Despite the skill and determination of electro-optical system designers, the images acquired using their best designs often suffer from blur and noise. The aim of an “image enhancer” such as myself is to improve these poor images, usually by digital means, such that they better resemble the true, “optical object,” input to the system. This problem is notoriously “ill-posed,” i.e. any direct approach at inversion of the image data suffers strongly from the presence of even a small amount of noise in the data. In fact, the fluctuations engendered in neighboring output values tend to be strongly negative-correlated, so that the output spatially oscillates up and down, with large amplitude, about the true object. What can be done about this situation? As we shall see, various concepts taken from statistical communication theory have proven to be of real use in attacking this problem. We offer below a brief summary of these concepts.


Author(s):  
Stuart McKernan

For many years the concept of quantitative diffraction contrast experiments might have consisted of the determination of dislocation Burgers vectors using a g.b = 0 criterion from several different 2-beam images. Since the advent of the personal computer revolution, the available computing power for performing image-processing and image-simulation calculations is enormous and ubiquitous. Several programs now exist to perform simulations of diffraction contrast images using various approximations. The most common approximations are the use of only 2-beams or a single systematic row to calculate the image contrast, or calculating the image using a column approximation. The increasing amount of literature showing comparisons of experimental and simulated images shows that it is possible to obtain very close agreement between the two images; although the choice of parameters used, and the assumptions made, in performing the calculation must be properly dealt with. The simulation of the images of defects in materials has, in many cases, therefore become a tractable problem.


Problems when calculating reinforced concrete structures based on the concrete deformation under compression diagram, which is presented both in Russian and foreign regulatory documents on the design of concrete and reinforced concrete structures are considered. The correctness of their compliance for all classes of concrete remains very approximate, especially a significant difference occurs when using Euronorm due to the different shape and sizes of the samples. At present, there are no methodical recommendations for determining the ultimate relative deformations of concrete under axial compression and the construction of curvilinear deformation diagrams, which leads to limited experimental data and, as a result, does not make it possible to enter more detailed ultimate strain values into domestic standards. The results of experimental studies to determine the ultimate relative deformations of concrete under compression for different classes of concrete, which allowed to make analytical dependences for the evaluation of the ultimate relative deformations and description of curvilinear deformation diagrams, are presented. The article discusses various options for using the deformation model to assess the stress-strain state of the structure, it is concluded that it is necessary to use not only the finite values of the ultimate deformations, but also their intermediate values. This requires reliable diagrams "s–e” for all classes of concrete. The difficulties of measuring deformations in concrete subjected to peak load, corresponding to the prismatic strength, as well as main cracks that appeared under conditions of long-term step loading are highlighted. Variants of more accurate measurements are proposed. Development and implementation of the new standard GOST "Concretes. Methods for determination of complete diagrams" on the basis of the developed method for obtaining complete diagrams of concrete deformation under compression for the evaluation of ultimate deformability of concrete under compression are necessary.


2016 ◽  
Vol 136 (8) ◽  
pp. 1120-1127 ◽  
Author(s):  
Naoya Ikemoto ◽  
Kenji Terada ◽  
Yuta Takashina ◽  
Akio Nakano

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