Image moments-based structuring and tracking of objects

Rocha, Leonardo Marques; Velho, Luiz; Carvalho, P.C.P.

doi:10.1109/sibgra.2002.1167130

Cited by 40 publications

(21 citation statements)

References 7 publications

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“…This in comparison to no significant differences for cell area, orientation, height and shape factor on all three images obtained with the CDA. Further, any CDA output image can be processed with existent software to assess more complex parameters for object and pattern assessment ([35] – [38]).…”

Section: Discussionmentioning

confidence: 99%

Automated Cell Detection and Morphometry on Growth Plate Images of Mouse Bone

Ascenzi¹,

Du²,

Harding³

et al. 2014

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Microscopy imaging of mouse growth plates is extensively used in biology to understand the effect of specific molecules on various stages of normal bone development and on bone disease. Until now, such image analysis has been conducted by manual detection. In fact, when existing automated detection techniques were applied, morphological variations across the growth plate and heterogeneity of image background color, including the faint presence of cells (chondrocytes) located deeper in tissue away from the image’s plane of focus, and lack of cell-specific features, interfered with identification of cell. We propose the first method of automated detection and morphometry applicable to images of cells in the growth plate of long bone. Through ad hoc sequential application of the Retinex method, anisotropic diffusion and thresholding, our new cell detection algorithm (CDA) addresses these challenges on bright-field microscopy images of mouse growth plates. Five parameters, chosen by the user in respect of image characteristics, regulate our CDA. Our results demonstrate effectiveness of the proposed numerical method relative to manual methods. Our CDA confirms previously established results regarding chondrocytes’ number, area, orientation, height and shape of normal growth plates. Our CDA also confirms differences previously found between the genetic mutated mouse Smad1/5CKO and its control mouse on fluorescence images. The CDA aims to aid biomedical research by increasing efficiency and consistency of data collection regarding arrangement and characteristics of chondrocytes. Our results suggest that automated extraction of data from microscopy imaging of growth plates can assist in unlocking information on normal and pathological development, key to the underlying biological mechanisms of bone growth.

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Section: Discussionmentioning

confidence: 99%

Automated Cell Detection and Morphometry on Growth Plate Images of Mouse Bone

Ascenzi¹,

Du²,

Harding³

et al. 2014

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“…Principal Component Analysis (PCA) is applied to the 2D projected points onto the local xy-plane, for finding the enclosing boundary. A closedform solution [67] for the corresponding eigendecomposition problem using 1D and 2D moments to fit approximate boundaries is used.…”

Section: Patch Fittingmentioning

confidence: 99%

Curved patch mapping and tracking for irregular terrain modeling: Application to bipedal robot foot placement

Kanoulas

Tsagarakis

Vona

2019

Robotics and Autonomous Systems

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Legged robots need to make contact with irregular surfaces, when operating in unstructured natural terrains. Representing and perceiving these areas to reason about potential contact between a robot and its surrounding environment, is still largely an open problem. This paper introduces a new framework to model and map local rough terrain surfaces, for tasks such as bipedal robot foot placement. The system operates in real-time, on data from an RGB-D and an IMU sensor. We introduce a set of parametrized patch models and an algorithm to fit them in the environment. Potential contacts are identified as bounded curved patches of approximately the same size as the robot's foot sole. This includes sparse seed point sampling, point cloud neighborhood search, and patch fitting and validation. We also present a mapping and tracking system, where patches are maintained in a local spatial map around the robot as it moves. A bio-inspired sampling algorithm is introduced for finding salient contacts. We include a dense volumetric fusion layer for spatiotemporally tracking, using multiple depth data to reconstruct a local point cloud. We present experimental results on a mini-biped robot that performs foot placements on rocks, implementing a 3D foothold perception system, that uses the developed patch mapping and tracking framework.Index Terms-irregular surface modeling, foothold contact modeling, bounded curved patch modeling, curved patch fitting and tracking, 3D perception for bipedal robots, bipedal robot foot placement, rough terrain stepping, legged robot locomotion ! • Dimitrios Kanoulas and Nikos G. Tsagarakis are with the Humanoids and

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“…This would require a bounding box update on every event added to or removed from a support region which is computationally expensive. The line segments in ELiSeD are therefore approximated by the major elliptic axis computed from the image moment of the support region [18] which can be computed efficiently according to [19]. end while…”

Section: B Support Regions and Line Fittingmentioning

confidence: 99%