Laplace gradient based Discriminative and Contrast Invertible descriptor

Miao, Zhenwei; Yap, Kim–Hui; Jiang, Xudong; Sinduja, Subbhuraam; Wang, Zhenhua

doi:10.1109/icassp.2017.7952475

Cited by 3 publications

(1 citation statement)

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“…Moreover, the bloblike structures widely spread over a pictorial image. These properties make the blob-like structure suitable in anchoring the local descriptor [23], [9] under various image conditions. Hence, a lot of works have been proposed to extract bloblike structures from images [9], [12], [18], [24].…”

Section: A Problem Formulationmentioning

confidence: 99%

Interest Point Detection based on Adaptive Ternary Coding

Miao,

Yap,

Jiang

2019

Preprint

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In this paper, an adaptive pixel ternary coding mechanism is proposed and a contrast invariant and noise resistant interest point detector is developed on the basis of this mechanism. Every pixel in a local region is adaptively encoded into one of the three statuses: bright, uncertain and dark. The blob significance of the local region is measured by the spatial distribution of the bright and dark pixels. Interest points are extracted from this blob significance measurement. By labeling the statuses of ternary bright, uncertain, and dark, the proposed detector shows more robustness to image noise and quantization errors. Moreover, the adaptive strategy for the ternary cording, which relies on two thresholds that automatically converge to the median of the local region in measurement, enables this coding to be insensitive to the image local contrast. As a result, the proposed detector is invariant to illumination changes. The state-of-the-art results are achieved on the standard datasets, and also in the face recognition application.

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