Image Segmentation Based on a Two-Dimensional Histogram

Lhoussaine, Masmoudi; Zennouhi, Rachid; Ansari, Mohamed El

doi:10.5772/15316

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…Occupancy and firing rate maps were estimated based on a spatial bin division shown in Fig. 4b, c, (place bins n = 84, view fields n = 106) per recording session 162 . Bins that weren't sampled more than 3 independent times, or <200 ms were discarded.…”

Section: Spatial Information Contentmentioning

confidence: 99%

Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus

Piza,

Corrigan,

Gulli

et al. 2024

Nat Commun

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The role of the hippocampus in spatial navigation has been primarily studied in nocturnal mammals, such as rats, that lack many adaptations for daylight vision. Here we demonstrate that during 3D navigation, the common marmoset, a new world primate adapted to daylight, predominantly uses rapid head-gaze shifts for visual exploration while remaining stationary. During active locomotion marmosets stabilize the head, in contrast to rats that use low-velocity head movements to scan the environment as they locomote. Pyramidal neurons in the marmoset hippocampus CA3/CA1 regions predominantly show mixed selectivity for 3D spatial view, head direction, and place. Exclusive place selectivity is scarce. Inhibitory interneurons are predominantly mixed selective for angular head velocity and translation speed. Finally, we found theta phase resetting of local field potential oscillations triggered by head-gaze shifts. Our findings indicate that marmosets adapted to their daylight ecological niche by modifying exploration/navigation strategies and their corresponding hippocampal specializations.

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Section: Spatial Information Contentmentioning

confidence: 99%

Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus

Piza,

Corrigan,

Gulli

et al. 2024

Nat Commun

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show abstract

“…Image segmentation is a fundamental and key technology in image processing and an important part of automatic target recognition [1]. Among the many segmentation methods, the thresholding method is one of the more widely used methods because of its simplicity, effectiveness, small computation, and stable performance [2]. Moreover, the thresholding method is particularly effective for image segmentation where there is a strong contrast between the object and the background.…”

Section: Introductionmentioning

confidence: 99%

Two-dimensional Otsu’s Zigzag Thresholding Segmentation Method

Liang

chen

2023

Preprint

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In the two-dimensional histogram thresholding method, the segmentation accuracy could be degraded due to insufficient misclassification. An improved image segmentation method combining a priori knowledge of two-dimensional histogram and fully considering the influence of edges, the two-dimensional Otsu’s zigzag thresholding segmentation method is proposed. We combine a priori information about the edge regions and noisy regions in a two-dimensional histogram, use a zigzag threshold as a segmentation criterion to correct the overall error classification and use small probability events to determine the line equations to achieve segmentation adaptively. Based on extensive experimentation, our method has been observed to significantly outperform comparable techniques.

show abstract

Image Segmentation Based on a Two-Dimensional Histogram

Cited by 2 publications

References 26 publications

Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus

Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus

Two-dimensional Otsu’s Zigzag Thresholding Segmentation Method

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