Segmenting color image of plants with a spatio-colorimetric approach

An unsupervised vectorial segmentation method using both spatial and color information is presented. To overcome the problem of memory space, this method is based on a multidimensional compact histogram and an original compact spatial neighborhood probability matrix (SNPM). The multidimensional compact histogram allows a drastic reduction of memory space without any data loss. Leaning upon the compact histogram, a SNPM has been computed. It contains all non-negative probabilities of spatial connectivity between pixel colors. In an unsupervised histogram analysis classification process, two phases are classically distinguished: (i) a learning process during which histogram modes are identified and (ii) a second step called the decision step in which a full partition of the colorimetric space is carried out according the previously defined classes. During the second step of a standard colorimetric approach, a colorimetric distance like Euclidean or Mahalanobis is used. We insert here a spatio-colorimetric distance defined as a weighed mixture between a colorimetric distance and the spatial distance calculated from the SNPM. The vectorial classification method is based on previously presented principles, achieving a hierarchical analysis of the color histogram by means of a 3D-connected components labeling. Results are applied to color images of plants to separate plantlets and loam

Towards an automated approach to map flooded areas from Sentinel-2 MSI data and soft integration of water spectral features

Abstract In this work we propose an approach for mapping flooded areas from Sentinel-2 MSI (Multispectral Instrument) data based on soft fuzzy integration of evidence scores derived from both band combinations (i.e. Spectral Indices - SIs) and components of the Hue, Saturation and Value (HSV) colour transformation. Evidence scores are integrated with Ordered Weighted Averaging (OWA) operators, which model user's decision attitude varying smoothly between optimistic and pessimistic approach. Output is a map of global evidence degree showing the plausibility of being flooded for each pixel of the input Sentinel-2 (S2) image. Algorithm set up and validation were carried out with data over three sites in Italy where water surfaces are extracted from stable water bodies (lakes and rivers), natural hazard flooding, and irrigated paddy rice fields. Validation showed more than satisfactory accuracy for the OR-like OWA operators (F-score > 0.90) with performance slightly decreased (F-scor

Kentucky Water Resources Research Institute Annual Technical Report FY 2011

The FY2011 Annual Technical Report for Kentucky consolidates reporting requirements for the Section 104(b) base grant award into a single document that includes; 1) a synopsis of each research project that was conducted during the period, 2) citations for related publications, reports, and presentations, 3) a description of information transfer activities, 4) a summary of student support during the reporting period, and 5) notable awards and achievements during the year. Project 2011KY166B (Sewage to fertilizer: a proposed solution to water pollution) was not initiated because the principal investigator (Dr. Rebecca Evans Kelley) resigned from the Department of Biological Sciences at Northern Kentucky University between the time the application was originally submitted and when funding was eventually made available through the program to conduct the project. As a result, the project was cancelled, no research was conducted, and no report for this project is provided. Project 2011KY213B (Use of gene expression in longear sunfish (Lepomis megalotis) and green sunfish (Lepomis cyanellus) as a biomarker of polychlorinated biphenyl and metal exposure) was delayed in starting. As a result, no significant progress was completed during FY 2011. The project report will be included in the FY 2012 Annual Technical Report

The influence of OsAUX1 on root system architecture and phosphorus uptake in rice (Oryza sativa)

Rice (Oryza sativa L.) provides up to 50% of the total calories consumed in countries such as India, Madagascar and Nigeria. As a crop, rice can require significant fertiliser inputs to maintain the required yields. Additionally, climate change has increased the need for rice varieties with improved drought resistance, tolerance to pests and more efficient acquisition of nutrients from soil. One major fertiliser input for rice is phosphate; reducing phosphorus (P) fertiliser use would have environmental and economic implications. Root traits linked to P acquisition in crops include shallow root angle, lateral root proliferation and increases in root hair length and density. Two T-DNA knockout alleles with reduced gravitropic response, Osaux1-1 and Osaux1-2, were used to investigate the influence of shallow root angle on P uptake. OsAUX1 is a rice ortholog for the Arabidopsis thaliana gene AUX1, which controls lateral root growth and gravitropic response. The wildtype and mutant rice plants were grown in soil and non-destructively imaged using X-ray micro Computed Tomography (X-ray CT). In Chapter Three, visualisation of rice roots in soil using X-ray CT was optimised by determining the ideal soil moisture content that would produce the best images. Water in soils has a similar X- ray attenuation density to that of plant roots and can influence segmentation of roots from soil in X-ray CT images. It was found that soil at nominal field capacity (ca. 3 days of drainage) produced the best contrast between soil fractions (organic matter, minerals and pore space) and root material. In Chapter Four, the impact of X-ray dose on root growth was quantified because the experimental design included repeated scanning of the same sample (Chapter Five). It was found that even under repeated scanning, the X-ray doses involved in this work (ca. 15 Gy per sample) did not significantly affect the root architecture and overall plant growth in rice cultivars used. In Chapter Five, Osaux1-1 and Osaux1-2 retained the agravitropic phenotype that was observed on agar-based systems when plants were grown in loamy sand soil. However, when subject to various soil P concentrations and distributions (Chapter Six), Osaux1-1 had similar gravitropic response and P uptake as wildtype. It was unclear what role gravitropism and topsoil foraging played in P uptake for these rice cultivars, if any. OsAUX1 could be linked to P uptake as well as responses to soil P concentration and distribution. Under uniformly low soil P wildtype had a shallower root system distribution than Osaux1-1. Of most interest were the results when sufficient soil P was sequestered to the top 4 cm of the soil column and low P was maintained in the bottom 6 cm. Under these conditions, wildtype took up more overall P, had almost twice the biomass, twice the total root length and twice the surface area when compared to Osaux1-1. This provides evidence that OsAUX1 can be linked to adaptation to P stress and distribution of P in soil through control of fine root characteristics and not necessarily its impact on gravitropic response. Chapter Seven describes the investigation into the impact of OsAUX1 on sub-architectural effects of the root system that could influence P uptake. It was determined that OsAUX1 was involved in root hair density and elongation under varying P availability for agar grown plants. In comparison to wildtype, Osaux1-1 had significant variation in root hair phenotype that seemed unrelated to a P stress response. In flooded environments, root hairs influence the potential for root:soil contact that is integral to P uptake in rice paddies which have reduced soil conditions and mass water flow that can transport plant available soluble P. This reinforces the potential for an interaction between OsAUX1 and P uptake in paddy rice

The influence of OsAUX1 on root system architecture and phosphorus uptake in rice (Oryza sativa)

Rice (Oryza sativa L.) provides up to 50% of the total calories consumed in countries such as India, Madagascar and Nigeria. As a crop, rice can require significant fertiliser inputs to maintain the required yields. Additionally, climate change has increased the need for rice varieties with improved drought resistance, tolerance to pests and more efficient acquisition of nutrients from soil. One major fertiliser input for rice is phosphate; reducing phosphorus (P) fertiliser use would have environmental and economic implications. Root traits linked to P acquisition in crops include shallow root angle, lateral root proliferation and increases in root hair length and density. Two T-DNA knockout alleles with reduced gravitropic response, Osaux1-1 and Osaux1-2, were used to investigate the influence of shallow root angle on P uptake. OsAUX1 is a rice ortholog for the Arabidopsis thaliana gene AUX1, which controls lateral root growth and gravitropic response. The wildtype and mutant rice plants were grown in soil and non-destructively imaged using X-ray micro Computed Tomography (X-ray CT). In Chapter Three, visualisation of rice roots in soil using X-ray CT was optimised by determining the ideal soil moisture content that would produce the best images. Water in soils has a similar X- ray attenuation density to that of plant roots and can influence segmentation of roots from soil in X-ray CT images. It was found that soil at nominal field capacity (ca. 3 days of drainage) produced the best contrast between soil fractions (organic matter, minerals and pore space) and root material. In Chapter Four, the impact of X-ray dose on root growth was quantified because the experimental design included repeated scanning of the same sample (Chapter Five). It was found that even under repeated scanning, the X-ray doses involved in this work (ca. 15 Gy per sample) did not significantly affect the root architecture and overall plant growth in rice cultivars used. In Chapter Five, Osaux1-1 and Osaux1-2 retained the agravitropic phenotype that was observed on agar-based systems when plants were grown in loamy sand soil. However, when subject to various soil P concentrations and distributions (Chapter Six), Osaux1-1 had similar gravitropic response and P uptake as wildtype. It was unclear what role gravitropism and topsoil foraging played in P uptake for these rice cultivars, if any. OsAUX1 could be linked to P uptake as well as responses to soil P concentration and distribution. Under uniformly low soil P wildtype had a shallower root system distribution than Osaux1-1. Of most interest were the results when sufficient soil P was sequestered to the top 4 cm of the soil column and low P was maintained in the bottom 6 cm. Under these conditions, wildtype took up more overall P, had almost twice the biomass, twice the total root length and twice the surface area when compared to Osaux1-1. This provides evidence that OsAUX1 can be linked to adaptation to P stress and distribution of P in soil through control of fine root characteristics and not necessarily its impact on gravitropic response. Chapter Seven describes the investigation into the impact of OsAUX1 on sub-architectural effects of the root system that could influence P uptake. It was determined that OsAUX1 was involved in root hair density and elongation under varying P availability for agar grown plants. In comparison to wildtype, Osaux1-1 had significant variation in root hair phenotype that seemed unrelated to a P stress response. In flooded environments, root hairs influence the potential for root:soil contact that is integral to P uptake in rice paddies which have reduced soil conditions and mass water flow that can transport plant available soluble P. This reinforces the potential for an interaction between OsAUX1 and P uptake in paddy rice

Fine Art Pattern Extraction and Recognition

This is a reprint of articles from the Special Issue published online in the open access journal Journal of Imaging (ISSN 2313-433X) (available at: https://www.mdpi.com/journal/jimaging/special issues/faper2020)

Deep Learning Methods for Remote Sensing

Remote sensing is a field where important physical characteristics of an area are exacted using emitted radiation generally captured by satellite cameras, sensors onboard aerial vehicles, etc. Captured data help researchers develop solutions to sense and detect various characteristics such as forest fires, flooding, changes in urban areas, crop diseases, soil moisture, etc. The recent impressive progress in artificial intelligence (AI) and deep learning has sparked innovations in technologies, algorithms, and approaches and led to results that were unachievable until recently in multiple areas, among them remote sensing. This book consists of sixteen peer-reviewed papers covering new advances in the use of AI for remote sensing

Advances in Image Processing, Analysis and Recognition Technology

For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches