Unsupervised Segmentation Method of Multicomponent Images Based on Fuzzy Connectivity Analysis in the Multidimensional Histograms

Image segmentation denotes a process for partitioning an image into distinct regions, it plays an important role in interpretation and decision making. A large variety of segmentation methods has been developed; among them, multidimensional histogram methods have been investigated but their implementation stays difficult due to the big size of histograms. We present an original method for segmenting n-D (where n is the number of components in image) images or multidimensional images in an unsupervised way using a fuzzy neighbourhood model. It is based on the hierarchical analysis of full n-D compact histograms integrating a fuzzy connected components labelling algorithm that we have realized in this work. Each peak of the histogram constitutes a class kernel, as soon as it encloses a number of pixels greater than or equal to a secondaryarbitrary threshold knowing that a first threshold was set to define the degree of binary fuzzy similarity between pixels. The use of a lossless compact n-D histogram allows a drastic reduction of the memory space necessary for coding it. As a consequence, the segmentation can be achieved without reducing the colors population of images in the classification step. It is shown that using n-D compact histograms, instead of 1-D and 2-D ones, leads to better segmentation results. Various images were segmented; the evaluation of the quality of segmentation in supervised and unsupervised of segmentation method proposed compare to the classification method k-means gives better results. It thus highlights the relevance of our approach, which can be used for solving many problems of segmentation

The Image Analysis, Tools for Measuring Quality Criteria of Apples by Characterization of its Cellular Structure

The measure of the quality of fruits is an economic stake and of human health. The tools for estimating the quality of fruit are still limited. Each tool provides a partial approach; it is the case of the colorimeter, the sound level meter, the penetrometer, etc. The assessment of the quality of fruit resulted from the combination of qualitative and quantitative measures. Histology and image analysis open up new fields of investigation by examining the internal structures of fruits and accurately locating the compounds involved in the development of quality. The work undertaken aims to develop methods for measuring the thickness of the cuticle, size and density of cells and cell walls of apple. We show here that the image analysis of histological sections is full of potential solutions allowing to better understanding the differences in texture and firmness or crispness among the three varieties of apples are examined as Braeburn, Fuji and the Golden Delicious. The materials and methods used to demonstrate are described. The results are presented and analyzed

A New Vectorial Order Approach Based on the Classification of Tuples Attribute and Relative Absolute Adaptive Referent: Applications to Multicomponent Images

In this paper, we are presenting a new vector order, a solution to the open problem of the generalization of mathematical morphology to multicomponent images and multidimensional data. This approach uses the paradigm of P?order. Its primary principle consists, first in partitioning the multi-com- ponent image in the attribute space by a classification method in different numbers of classes, and then the vector attributes are ordered within each class (intra-order-class). And finally the classes themselves are ordered in turn from their barycenter (inter-class order). Thus, two attribute vectors (or colors) whatever, belonging to the vector image can be compared. Provided with this relation of order, vectors attributes of a multivariate image define a complete lattice ingredient necessary for the definition of the various morphological operators. In fact, this method creates a strong close similarity between vectors in order to move towards an order of the same principle as defined in the set of real numbers. The more the number of classes increases, the more the colors of the same class are similar and therefore the absolute adaptive referent tends to be optimal. On the other hand, the more the class number decreases or equals two, the more our approach tends towards the hybrid order developed previously. The proposed order has been implemented on different morphological operators through different multicomponent images. The fundamental robustness of our approach and that relating to noise have been tested. The results on the gradient, Laplacian and Median filter operators show the performance of our new order

Analysis of the Relevance of Evaluation Criteria for Multicomponent Image Segmentation

Image segmentation is an important stage in many applications such as image, video and computer processing. Gener-ally image interpretation depends on it. The materials and methods used to demonstrate are described. The results are presented and analyzed. Several approaches and algorithms for image segmentation have been developed, but it is dif-ficult to evaluate the efficiency and to make an objective comparison of different segmentation methods. This general problem has been addressed for the evaluation of a segmentation result and the results are available in the literature. In this work, we first presented some criteria of evaluation of segmentation commonly used in image processing with reviews of their models. Then multicomponent synthetic images of known composition are applied to these criteria to explore the operation and evaluate its relevance. The results show that choosing an assessment method depends on the purpose, however the criterion of Zeboudj appears powerful for the evaluation of region segmentations for properly separated classes, on the contrary the criteria of Levine-Nazif and Borsotti are adapted to the methods of classification and permit to build homogeneous regions or classes. The values of the Rosenbeger criterion are generally low and similar, so hard to make a comparison of segmentations with this criterion

A New Hybrid Order Approach to Morphological Color Image Processing Based on Reduced Order with Adaptive Absolute Reference

Mathematical morphology can process the binary and grayscale image successfully. This theory cannot be extended to the color image directly. In color space, a vector represents a pixel, so in order to compare vectors, vectoriel orderings must be defined first. This paper addresses the question of the extension of morphological operator to the case of color images. The proposed method used the order by bit mixing to replace the conditional order. Our order is based on a combination of reduced and bit mixing ordering of the underlying data. Additionally it is a total ordering. Since it not only solves the problems of false color generated by the marginal order but also those of multiple extrema generated by reduced order. The performance of the introduced operators is illustrated by means of different applications: color gradients for segmenting, image smoothing (noise suppression) by median filter operator and Laplacian operators. Examples of natural color images and synthetic color images are given. Experimental results show the improvement brought by this new method

Facility and community results-based financing to improve maternal and child nutrition and health in The Gambia

In 2013, the Government of The Gambia implemented a novel results-based financing (RBF) intervention designed to improve maternal and child nutrition and health through a combination of community, facility and individual incentives. In a mixed-methods study, we used a randomized 2 x 2 study design to measure these interventions' impact on the uptake of priority maternal health services, hygiene and sanitation. Conditional cash transfers to individuals were bundled with facility results-based payments. Community groups received incentive payments conditional on completion of locally-designed health projects. Randomization occurred separately at health facility and community levels. Our model pools baseline, midline and endline exposure data to identify evidence of the interventions' impact in isolation or combination. Multivariable linear regression models were estimated. A qualitative study was embedded, with data thematically analyzed. We analyzed 5,927 household surveys: 1,939 baseline, 1,951 midline, and 2,037 endline. On average, community group interventions increased skilled deliveries by 11 percentage points, while the facility interventions package increased them by seven percentage points. No impact was found, either in the community group or facility intervention package arms on early ANC. The community group intervention led to 49, 43 and 48 percentage point increases in handwashing stations, soaps at station and water at station, respectively. No impact was found on improved sanitation facilities. The qualitative data help understand factors underlying these changes. No interaction was found between the community and facility interventions. Where demand-side barriers predominate and community governance structures exist, community group RBF interventions may be more effective than facility designs

Feasibility and safety of integrating mass drug administration for helminth control with seasonal malaria chemoprevention among Senegalese children: a randomized controlled, observer-blind trial

BACKGROUND: The overlap in the epidemiology of malaria and helminths has been identified as a potential area to exploit for the development of an integrated control strategy that may help to achieve elimination of malaria and helminths. A randomized, controlled, observer-blind trial was conducted to assess the feasibility and safety of combining mass drug administration (MDA) for schistosomiasis and soil transmitted helminths (STH) with seasonal malaria chemoprevention (SMC) among children living in Senegal. METHODS: Female and male children aged 1-14 years were randomized 1:1:1, to receive Vitamin A and Zinc on Day 0, followed by SMC drugs (sulfadoxine-pyrimethamine and amodiaquine) on Days 1-3 (control group); or praziquantel and Vitamin A on Day 0, followed by SMC drugs on Days 1-3 (treatment group 1); or albendazole and praziquantel on Day 0, followed by SMC drugs on Days 1-3 (treatment group 2). Safety assessment was performed by collecting adverse events from all children for six subsequent days following administration of the study drugs. Pre- and post-intervention, blood samples were collected for determination of haemoglobin concentration, malaria microscopy, and PCR assays. Stool samples were analyzed using Kato-Katz, Merthiolate-iodine-formalin and PCR methods. Urine filtration, PCR and circulating cathodic antigen tests were also performed. RESULTS: From 9 to 22 June 2022, 627 children aged 1-14 years were randomized into the three groups described above. Mild, transient vomiting was observed in 12.6% (26/206) of children in treatment group 2, in 10.6% (22/207) in group 1, and in 4.2% (9/214) in the control group (p = 0.005). Pre-intervention, the geometric mean value of Plasmodium falciparum parasite density was highest among children who received albendazole, praziquantel with SMC drugs. Post-intervention, the parasite density was highest among children who received SMC drugs only. Children who received praziquantel and SMC drugs had a lower risk of developing severe anaemia than their counterparts who received SMC drugs alone (OR = 0.81, 95% CI 0.13-5.00, p = 0.63). CONCLUSIONS: Integration of MDA for helminths with SMC drugs was safe and feasible among Senegalese children. These findings support further evaluation of the integrated control model. TRIAL REGISTRATION: The study is registered at Clinical Trial.gov NCT05354258