Shape Prediction Linear Algorithm Using Fuzzy

Kaur, Navjot; Kundra, Sheetal; Kundra, Harish

doi:10.14569/ijacsa.2012.031011

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2018

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Cited by 2 publications

(1 citation statement)

References 10 publications

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“…We have used Canny edge detector, because it has numerous advantages in comparison with classical methods, such as Sobel, Prewitt and Roberts due to its option of defining a standard deviation threshold σ which produces an edge image related to input parameter σ. In addition, Canny has better performance on a noisy images and it uses a probability to find the error rates which causes more precision in detecting edges [9].…”

Section: Feature Extractionmentioning

confidence: 99%

Fast Content Based Color Image Retrieval System Based on Texture Analysis of Edge Map

Salehian

Zamani

Jamzad

2011

AMR

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In this paper we propose a method for CBIR based on the combination of texture, edge map and color. As texture of edges yields important information about the images, we utilized an adaptive edge detector that produces a binary edge image. Also, using the statistics of color in two different color spaces provides complementary information to retrieve images. Our method is time efficient since we have applied texture calculations on the binary edge image. Our experimental results showed both the higher accuracy and lower time complexity of our method with similar related works using SIMPLIcity database.

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Section: Feature Extractionmentioning

confidence: 99%