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7 articles for “Texture descriptors”
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Food Texture Descriptors: A Compilation of the most Important Terms used in Sensory Analyses
Abstract: The texture is essential in the quality and acceptance of food, being classified into three distinct groups: mechanical, geometrical, and compositional. The so-called “lexicons” are standardized vocabularies with the definitions and references for each attribute which aid the application of descriptive sensory analysis. The objective of this study was to raise typical texture descriptors from different types of food, relating them to the methodologies and technological processes used, besides the …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 9, Issue 3, 2020 · pp. 16–27 Read article
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A Statistical Approach Noise Tolerant Texture Classification
Abstract: A simple, efficient, yet robust multi resolution approach to texture classification binary rotation invariant and noise tolerant. The proposed approach is very fast to build and very compact while remaining robust to illumination variations, rotation changes, and noise. We have developed a novel and simple strategy to compute a local binary descriptor based on the conventional local binary pattern (LBP) approach, preserving the advantageous characteristics of uniform LBP. Points are …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 3, Issue 2, 2016 · pp. 14–19 Read article
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Content-based Image Retrieval using SURF Feature Point Descriptor and Local Binary Pattern with Color Histogram
Abstract: An important research issue in multimedia technology is the retrieval of similar objects. Most of the content-based image retrieval (CBIR) uses the low-level features such as color, shape and texture to extract the features from the images. A short time ago, the interest points are used to extract the most relevant images with different view point and transformations. Speed up Robust Feature (SURF) is robust and fast interest points detector/descriptor …
Published in Journal of Open Source Developments · Vol. 2, Issue 2, 2015 · pp. 9–15 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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CBIR using Feature Extraction approaches and Application: A survey
Abstract: Abstract—Content based-image retrieval (CBIR) is an extraordinarily foremost field of study at the moment. CBIR is a method which constructs use of visible facets of image corresponding to color, form, texture, and so on. CBIR technologies furnish an approach to discover images in enormous databases by way of using particular descriptors from an expert image. A lots of researches work had been accomplished prior to now decade to design resourceful …
Published in Journal Of Network security · Vol. 5, Issue 3, 2017 · pp. 9–16 Read article
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Image-Based Evaluation of Implant Tissue Interface Integrity in Polymer Orthopaedic Devices
Abstract: Polymer orthopedic implants offer radiolucency and mechanical compatibility with bone, but long-term success depends on maintaining a stable implant–tissue interface. Routine imaging is widely available for follow-up, yet interface integrity is commonly judged qualitatively, limiting early detection of fixation compromise and reducing comparability across devices and time points. This work presents an image-based methodology to quantify interface integrity by extracting interpretable interface descriptors from a standardized interface belt around the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 170–179 Read article
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Color and Texture Features Based Object Recognition Using Machine Learning Methods
Abstract: Object recognition in images is a simple task for human but it is a complex and challenging task for machines due to different factors such as occlusion, lightening, object size, scaling etc. A Robust and automatic image processing system is thus critically required to make such a sampling approach practical. In this paper, we propose a method for classification of objects in images by incorporating global descriptors of the image …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 2, 2018 · pp. 1–11 Read article