990 resultados para color features
Resumo:
In this paper a new method for image retrieval using high level color semantic features is proposed. It is based on extraction of low level color characteristics and their conversion into high level semantic features using Johannes Itten theory of color, Dempster-Shafer theory of evidence and fuzzy production rules.
Classification of Paintings by Artist, Movement, and Indoor Setting Using MPEG-7 Descriptor Features
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ACM Computing Classification System (1998): I.4.9, I.4.10.
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PURPOSE: To quantitatively analyze and compare the fundoscopic features between fellow eyes of retinal angiomatous proliferation and typical exudative age-related macular degeneration and to identify possible predictors of neovascularization. METHODS: Retrospective case-control study. Seventy-nine fellow eyes of unilateral retinal angiomatous proliferation (n = 40) and typical exudative age-related macular degeneration (n = 39) were included. Fundoscopic features of the fellow eyes were assessed using digital color fundus photographs taken at the time of diagnosis of neovascularization in the first affected eye. Grading was performed by two independent graders using RetmarkerAMD, a computer-assisted grading software based on the International Classification and Grading System for age-related macular degeneration. RESULTS: Baseline total number and area (square micrometers) of drusen in the central 1,000, 3,000, and 6,000 μm were considerably inferior in the fellow eyes of retinal angiomatous proliferation, with statistically significant differences (P < 0.05) observed in virtually every location (1,000, 3,000, and 6,000 μm). A soft drusen (≥125 μm) area >510,196 μm2 in the central 6,000 μm was associated with an increased risk of neovascularization (hazard ratio, 4.35; 95% confidence interval [1.56-12.15]; P = 0.005). CONCLUSION: Baseline fundoscopic features of the fellow eye differ significantly between retinal angiomatous proliferation and typical exudative age-related macular degeneration. A large area (>510,196 μm2) of soft drusen in the central 6,000 μm confers a significantly higher risk of neovascularization and should be considered as a phenotypic risk factor.
Resumo:
PURPOSE: To quantitatively analyze and compare the fundoscopic features between fellow eyes of retinal angiomatous proliferation and typical exudative age-related macular degeneration and to identify possible predictors of neovascularization. METHODS: Retrospective case-control study. Seventy-nine fellow eyes of unilateral retinal angiomatous proliferation (n = 40) and typical exudative age-related macular degeneration (n = 39) were included. Fundoscopic features of the fellow eyes were assessed using digital color fundus photographs taken at the time of diagnosis of neovascularization in the first affected eye. Grading was performed by two independent graders using RetmarkerAMD, a computer-assisted grading software based on the International Classification and Grading System for age-related macular degeneration. RESULTS: Baseline total number and area (square micrometers) of drusen in the central 1,000, 3,000, and 6,000 μm were considerably inferior in the fellow eyes of retinal angiomatous proliferation, with statistically significant differences (P < 0.05) observed in virtually every location (1,000, 3,000, and 6,000 μm). A soft drusen (≥125 μm) area >510,196 μm2 in the central 6,000 μm was associated with an increased risk of neovascularization (hazard ratio, 4.35; 95% confidence interval [1.56-12.15]; P = 0.005). CONCLUSION: Baseline fundoscopic features of the fellow eye differ significantly between retinal angiomatous proliferation and typical exudative age-related macular degeneration. A large area (>510,196 μm2) of soft drusen in the central 6,000 μm confers a significantly higher risk of neovascularization and should be considered as a phenotypic risk factor.
Resumo:
The effectiveness of higher-order spectral (HOS) phase features in speaker recognition is investigated by comparison with Mel Cepstral features on the same speech data. HOS phase features retain phase information from the Fourier spectrum unlikeMel–frequency Cepstral coefficients (MFCC). Gaussian mixture models are constructed from Mel– Cepstral features and HOS features, respectively, for the same data from various speakers in the Switchboard telephone Speech Corpus. Feature clusters, model parameters and classification performance are analyzed. HOS phase features on their own provide a correct identification rate of about 97% on the chosen subset of the corpus. This is the same level of accuracy as provided by MFCCs. Cluster plots and model parameters are compared to show that HOS phase features can provide complementary information to better discriminate between speakers.