Extraction and characterisation of pectin from dragon fruit (hylocereus polyrhizus) peels

Pectins are complex carbohydrate molecules that are used in numerous food applications as a gelling agent, thickener, stabiliser, and emulsifier. Dragon fruit (Hylocereus polyrhizus) is one of the tropical fruits that belong to the cactus family, Cactaceae. Since the peels of dragon fruit are often discarded as waste, it would be an advantage to convert it into a value-added product such as pectin. The objective of this study was to investigate the extraction of pectin from dragon fruit peels under different extraction time using hot water extraction method. The dragon fruit peels were extracted using distilled water at 80 °C with different extraction time of 20, 40, 60 and 80 min. The extracted pectin was characterised by its yield, moisture and ash content, degree of esterification and antioxidant activity. Determination of moisture and ash content was conducted using AOAC standard method. The determination of the degree of esterification of pectin was performed using Fourier Transform Infrared Spectroscopy (FTIR). DPPH assay was used to determine the antioxidant activity of the pectin extract. Based on the result, the yield of pectin decreases (20.34 to 16.20 %) with the increase of extraction time, moisture contents were between 4 to 6 % while ash contents were between 7 to 10 %. Pectin from dragon fruit peels was determined as low methoxyl pectin and has high percentage of antioxidant activity with low value of inhibition concentration (IC50) (0.0063 to 0.0080 mg/mL). 60 min extraction sample exhibits the highest antioxidant activity (81.91 % at 40 μg/mL), followed by 80 min extraction (81.68 % at 40 μg/mL), 40 min extraction (81.38 % at 40 μg/mL) and 20 min extraction (81.31 % at 40 μg/mL)

Cross-entropy based image thresholding

This paper presents a novel global thresholding algorithm for the binarization of documents and gray-scale images using Cross Entropy Clustering. In the first step, a gray-level histogram is constructed, and the Gaussian densities are fitted. The thresholds are then determined as the cross-points of the Gaussian densities. This approach automatically detects the number of components (the upper limit of Gaussian densities is required)

A Novel Approach to Threshold Quantum Images by using Unsharp Measurements

We propose a hybrid quantum approach to threshold and binarize a grayscale image through unsharp measurements (UM) relying on image histogram. Generally, the histograms are characterized by multiple overlapping normal distributions corresponding to objects, or image features with small but significant overlaps, making it challenging to establish suitable thresholds. The proposed methodology uses peaks of the overlapping Gaussians and the distance between neighboring local minima as the variance, based on which the UM parameters are chosen, that maps the normal distribution into a localized delta function. To demonstrate its efficacy, subsequent implementation is done on noisy quantum environments in Qiskit. This process is iteratively repeated for a multimodal histogram to obtain more thresholds, which are then applied to various life-like pictures to get high-contrast images, resulting in comparable peak signal-to-noise ratio and structural similarity index measure values. The obtained thresholds are used to binarize a grayscale image by using novel enhanced quantum image representation integrated with a threshold encoder and an efficient quantum comparator (QC) that depicts the whole binarized picture. This approach significantly reduces the complexity of the proposed QC and of the whole algorithm when compared to earlier models

Técnicas de umbralización para el procesamiento digital de imágenes de GEM-Foils

A GEM-Foil (Gas Electron Multiplier - Foil) is a basic component of new radiation detectors used mainly in high energy physics and nuclear physics experiments. Optimum performance of such detectors depends critically on the quality of manufacture of such component, because any irregularity in one of the hundreds of thousands of micro-perforations in the plate can induce a spark during operation and damage the detector. Currently, in order to assess the quality of a GEM-Foil, high resolution images are acquired through optical systems to be digitized and then examined by visual inspection. In this work, various techniques to perform binarization of the images of the GEM-Foils are compared, by applying techniques of global and local thresholding, in order to improve the speed and efficiency of processing the images of the GEM-Foils for its quality control. From tests it was found that by simple statistical calculations as the average of the maximum and minimum intensity, using local adaptive thresholding is possible to carry out the segmentation of images in an efficient manner without having to use more complex methods which may involve too large process time.Una GEM-Foil (Gas Electron Multiplier - Foil) es un componente básico de nuevos detectores de radiación usados principalmente en experimentos de física de altas energías y física nuclear. El desempeño óptimo de tales detectores depende críticamente de la calidad de fabricación de dicho componente, ya que cualquier irregularidad en una de las cientos de miles de micro-perforaciones de la placa puede inducir una chispa durante el funcionamiento y dañar el detector. Actualmente, para evaluar la calidad de fabricación de una GEM-Foil se adquieren imágenes de alta resolución mediante sistemas ópticos que las digitalizan para ser luego examinadas por inspección visual. En este trabajo se comparan varias técnicas para realizar la binarización de las imágenes de las GEM-Foils, aplicando técnicas de umbralización global y local, con el propósito de mejorar la rapidez y eficiencia del procesamiento  de las imágenes de las GEM-Foils para realizar posteriormente su control de calidad. A partir de las pruebas realizadas se encontró que mediante cálculos  estadísticos simples, como el promedio del máximo y mínimo de intensidad, aplicando umbralización local adaptativa es posible realizar la segmentación de las imágenes de una manera eficiente sin tener que recurrir a métodos más complejos los cuales pueden implicar tiempos de proceso demasiado grandes

Técnicas de umbralización para el procesamiento digital de imágenes de GEM-Foils

A GEM-Foil (Gas Electron Multiplier - Foil) is a basic component of new radiation detectors used mainly in high energy physics and nuclear physics experiments. Optimum performance of such detectors depends critically on the quality of manufacture of such component, because any irregularity in one of the hundreds of thousands of micro-perforations in the plate can induce a spark during operation and damage the detector. Currently, in order to assess the quality of a GEM-Foil, high resolution images are acquired through optical systems to be digitized and then examined by visual inspection. In this work, various techniques to perform binarization of the images of the GEM-Foils are compared, by applying techniques of global and local thresholding, in order to improve the speed and efficiency of processing the images of the GEM-Foils for its quality control. From tests it was found that by simple statistical calculations as the average of the maximum and minimum intensity, using local adaptive thresholding is possible to carry out the segmentation of images in an efficient manner without having to use more complex methods which may involve too large process time.Una GEM-Foil (Gas Electron Multiplier - Foil) es un componente básico de nuevos detectores de radiación usados principalmente en experimentos de física de altas energías y física nuclear. El desempeño óptimo de tales detectores depende críticamente de la calidad de fabricación de dicho componente, ya que cualquier irregularidad en una de las cientos de miles de micro-perforaciones de la placa puede inducir una chispa durante el funcionamiento y dañar el detector. Actualmente, para evaluar la calidad de fabricación de una GEM-Foil se adquieren imágenes de alta resolución mediante sistemas ópticos que las digitalizan para ser luego examinadas por inspección visual. En este trabajo se comparan varias técnicas para realizar la binarización de las imágenes de las GEM-Foils, aplicando técnicas de umbralización global y local, con el propósito de mejorar la rapidez y eficiencia del procesamiento  de las imágenes de las GEM-Foils para realizar posteriormente su control de calidad. A partir de las pruebas realizadas se encontró que mediante cálculos  estadísticos simples, como el promedio del máximo y mínimo de intensidad, aplicando umbralización local adaptativa es posible realizar la segmentación de las imágenes de una manera eficiente sin tener que recurrir a métodos más complejos los cuales pueden implicar tiempos de proceso demasiado grandes

Técnicas de umbralización para el procesamiento digital de imágenes de GEM-Foils

A GEM-Foil (Gas Electron Multiplier - Foil) is a basic component of new radiation detectors used mainly in high energy physics and nuclear physics experiments. Optimum performance of such detectors depends critically on the quality of manufacture of such component, because any irregularity in one of the hundreds of thousands of micro-perforations in the plate can induce a spark during operation and damage the detector. Currently, in order to assess the quality of a GEM-Foil, high resolution images are acquired through optical systems to be digitized and then examined by visual inspection. In this work, various techniques to perform binarization of the images of the GEM-Foils are compared, by applying techniques of global and local thresholding, in order to improve the speed and efficiency of processing the images of the GEM-Foils for its quality control. From tests it was found that by simple statistical calculations as the average of the maximum and minimum intensity, using local adaptive thresholding is possible to carry out the segmentation of images in an efficient manner without having to use more complex methods which may involve too large process time.Una GEM-Foil (Gas Electron Multiplier - Foil) es un componente básico de nuevos detectores de radiación usados principalmente en experimentos de física de altas energías y física nuclear. El desempeño óptimo de tales detectores depende críticamente de la calidad de fabricación de dicho componente, ya que cualquier irregularidad en una de las cientos de miles de micro-perforaciones de la placa puede inducir una chispa durante el funcionamiento y dañar el detector. Actualmente, para evaluar la calidad de fabricación de una GEM-Foil se adquieren imágenes de alta resolución mediante sistemas ópticos que las digitalizan para ser luego examinadas por inspección visual. En este trabajo se comparan varias técnicas para realizar la binarización de las imágenes de las GEM-Foils, aplicando técnicas de umbralización global y local, con el propósito de mejorar la rapidez y eficiencia del procesamiento  de las imágenes de las GEM-Foils para realizar posteriormente su control de calidad. A partir de las pruebas realizadas se encontró que mediante cálculos  estadísticos simples, como el promedio del máximo y mínimo de intensidad, aplicando umbralización local adaptativa es posible realizar la segmentación de las imágenes de una manera eficiente sin tener que recurrir a métodos más complejos los cuales pueden implicar tiempos de proceso demasiado grandes

Unsupervised segmentation of road images. A multicriteria approach

This paper presents a region-based segmentation algorithm which can be applied to various problems since it does not requir e a priori knowledge concerning the kind of processed images . This algorithm, based on a split and merge method, gives reliable results both on homogeneous grey level images and on textured images . First, images are divided into rectangular sectors . The splitting algorithm works independently on each sector, and uses a homogeneity criterion based only on grey levels . The mergin g is then achieved through assigning labels to each region obtained by the splitting step, using extracted feature measurements . We modeled exploited fields (data field and label field) by Markov Random Fields (MRF), the segmentation is then optimall y determined using the Iterated Conditional Modes (ICM) . Input data of the merging step are regions obtained by the splitting step and their corresponding features vector. The originality of this algorithm is that texture coefficients are directly computed from these regions . These regions will be elementary sites for the Markov relaxation process . Thus, a region- based segmentation algorith m using texture and grey level is obtained . Results from various images types are presented .Nous présentons ici un algorithme de segmentation en régions pouvant s'appliquer à des problèmes très variés car il ne tient compte d'aucune information a priori sur le type d'images traitées. Il donne de bons résultats aussi bien sur des images possédant des objets homogènes au sens des niveaux de gris que sur des images possédant des régions texturées. C'est un algorithme de type division-fusion. Lors d'une première étape, l'image est découpée en fenêtres, selon une grille. L'algorithme de division travaille alors indépendamment sur chaque fenêtre, et utilise un critère d'homogénéité basé uniquement sur les niveaux de gris. La texture de chacune des régions ainsi obtenues est alors calculée. A chaque région sera associé un vecteur de caractéristiques comprenant des paramètres de luminance, et des paramètres de texture. Les régions ainsi définies jouent alors le rôle de sites élémentaires pour le processus de fusion. Celui-ci est fondé sur la modélisation des champs exploités (champ d'observations et champ d'étiquettes) par des champs de Markov. Nous montrerons les résultats de segmentation obtenus sur divers types d'images