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Showing 1 to 8 of 8 for “"Gray level co-occurrence matrix"”.

  1. Image Quality Analysis Using GLCM

    Gray level co-occurrence matrix has proven to be a powerful basis for use in texture classification. Various textural parameters calculated from the gray level co-occurrence matrix help understand the details about the overall image content. The aim of this research is to investigate the use of the …

    ucf

  2. Krūties vėžio magnetinio rezonanso vaizdo tekstūros analizė /

    … and to identify precise radiomic features that could develop new non-invasive breast cancer diagnostic approaches, oriented at genetics. Methods: A prospective analysis of MRI radiomic features and genetic data from 42 patients diagnosed with invasive ductal carcinoma was performed. The cohort …

    vilnius Repository record for Krūties vėžio magnetinio rezonanso vaizdo tekstūros analizė / (opens in a new tab)

  3. Early Forest Fire Detection Using Texture Analysis of Principal Components from Multispectral Video

    <p>The aim of this study is to incorporate the spectral, temporal and spatial attributes of a smoke plume for Early Forest Fire Detection. Image processing techniques are used on multispectral (red, green, blue, mid-wave infrared, and long-wave infrared) video to segment and indentify the presence …

    calpoly Repository record for Early Forest Fire Detection Using Texture Analysis of Principal Components from Multispectral Video (opens in a new tab)

  4. PROFILING EFFUSION CELLS BY QUANTITATIVE ANALYSIS OF MORPHOLOGY AND DIFFRACTION IMAGING PATTERNS

    … diagnosis of cancers and patient management. Conventional PPE cytology of a PPE sample is labor intensive and its efficacy depends heavily on the experience of trained specialists in addition to low sensitivity. In this dissertation research project, we focused our effort on application of a …

    ecu Repository record for PROFILING EFFUSION CELLS BY QUANTITATIVE ANALYSIS OF MORPHOLOGY AND DIFFRACTION IMAGING PATTERNS (opens in a new tab)

  5. Non-contact Methods for Detecting Hot-mix Asphalt Nonuniformity

    … quantify the presence of this problem in newly constructed pavements. Current practices are usually based on visual inspections that identify non-uniform surface texture areas. An automatic process that reduces subjectivity would improve the quality-assurance procedures of HMA pavements. …

    vt Repository record for Non-contact Methods for Detecting Hot-mix Asphalt Nonuniformity (opens in a new tab)

  6. Quantitative Texture Analysis and Automated Segmentation of Patellar Tendon Sonographic Images on Collegiate Athletes

    Patellar tendinopathy, a common cause of anterior knee pain, is primarily due to degenerative changes in the patellar tendon resulting from repetitive stress. While the tendon itself is the primary focus, damage can also manifest in surrounding tissues, such as the subcutaneous tissue and the fat …

    vt Repository record for Quantitative Texture Analysis and Automated Segmentation of Patellar Tendon Sonographic Images on Collegiate Athletes (opens in a new tab)

  7. Computer vision and texture analysis for characterization of X-ray images of rocks

    X-ray micro-computed tomography (micro-CT) has provided us digital twins of physical rocks. Digital twins are raw grayscale micro-CT images that contain information regarding rock-microstructure. These raw micro-CT images are then transformed into their segmented counterparts, which attempt to …

    unsw Repository record for Computer vision and texture analysis for characterization of X-ray images of rocks (opens in a new tab)

  8. Comparison of spatial and spectral properties of Landsat-8 and Sentinel-2 data for mapping plant chlorophyll-a

    … capacity to ensure proper flow of ecosystem services. Nowadays, with a rapid increase in human population and deforestation chl-a in higher plants remain at risk from degradation. Aim The study sought to compare the spatial and spectral properties Landsat-8 and Sentinel-2 in …

    venda Repository record for Comparison of spatial and spectral properties of Landsat-8 and Sentinel-2 data for mapping plant chlorophyll-a (opens in a new tab)