An Effective Implementation of Exudate Extraction from Fundus Images of the Eye for a Content Based Image Retrieval System Through Hardware Description Language

Gururaj, C.; Jayadevappa, D.; Tunga, Satish

doi:10.1007/978-81-322-2553-9_27

Cited by 6 publications

(1 citation statement)

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“…A UTOMATIC 3D geometric labeling or layout reasoning from a single scene image is one of the most important and challenging problems in scene understanding. It offers the mid-level information for other high-level scene understanding tasks such as 3D world reconstruction [1], [2], [3], [4], [5], [6], depth map estimation [7], [8], [9], scene classification [10], [11], [12] and content-based image retrieval [13], [14], [15].…”

Section: Introductionmentioning

confidence: 99%

GAL: A global-attributes assisted labeling system for outdoor scenes

Ren

Chen

et al. 2017

Journal of Visual Communication and Image Representation

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Abstract-An approach that extracts global attributes from outdoor images to facilitate geometric layout labeling is investigated in this work. The proposed Global-attributes Assisted Labeling (GAL) system exploits both local features and global attributes. First, by following a classical method, we use local features to provide initial labels for all super-pixels. Then, we develop a set of techniques to extract global attributes from 2D outdoor images. They include sky lines, ground lines, vanishing lines, etc. Finally, we propose the GAL system that integrates global attributes in the conditional random field (CRF) framework to improve initial labels so as to offer a more robust labeling result. The performance of the proposed GAL system is demonstrated and benchmarked with several state-of-the-art algorithms against a popular outdoor scene layout dataset.

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