Robust Estimation of Object Dimensions and External Defect Detection with a Low-Cost Sensor

Leo, Marco; Natale, Anna; Del-Coco, Marco; Carcagnì, Pierluigi; Distante, Cosimo

doi:10.1007/s10921-017-0395-7

Cited by 12 publications

(11 citation statements)

References 23 publications

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“…A method for the dimension measurement and inspection of cuboidal objects (boxes) with a ToF camera was described in [4], with an average error of 5 mm. The same ToF camera was used in [5] to build a system for computing the volume of cuboidal objects with an accuracy of 8 mm.…”

Section: Introductionmentioning

confidence: 99%

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Portable System for Box Volume Measurement Based on Line-Structured Light Vision and Deep Learning

Peng

Zhang

Song

et al. 2019

Sensors

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Portable box volume measurement has always been a popular issue in the intelligent logistic industry. This work presents a portable system for box volume measurement that is based on line-structured light vision and deep learning. This system consists of a novel 2 × 2 laser line grid projector, a sensor, and software modules, with which only two laser-modulated images of boxes are required for volume measurement. For laser-modulated images, a novel end-to-end deep learning model is proposed by using an improved holistically nested edge detection network to extract edges. Furthermore, an automatic one-step calibration method for the line-structured light projector is designed for fast calibration. The experimental results show that the measuring range of our proposed system is 100–1800 mm, with errors less than ±5.0 mm. Theoretical analysis indicates that within the measuring range of the system, the measurement uncertainty of the measuring device is ±0.52 mm to ±4.0 mm, which is consistent with the experimental results. The device size is 140 mm × 35 mm × 35 mm and the weight is 110 g, thus the system is suitable for portable automatic box volume measurement.

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Section: Introductionmentioning

confidence: 99%

“…The depth calculation accuracy of ToF does not change with the change in distance. The measurement accuracy can reach the mm level by using an advanced ToF camera and algorithm, as previously mentioned [4,5].…”

Section: Introductionmentioning

confidence: 99%

Portable System for Box Volume Measurement Based on Line-Structured Light Vision and Deep Learning

Peng

Zhang

Song

et al. 2019

Sensors

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“…In industrial applications, various computer vision methods, such as stereo vision [1,2], deep camera [3][4][5][6], and structured light [7,8], have been developed for 3D information measurement. Two effective approaches [5,6] automatically detect box objects and estimate their dimensions by using depth cameras based on TOF technology, with an average error of 8 and 5 mm, respectively. Peng et al [7] presented a box dimension measurement system based on multiline structure light vision, with errors of less than 5 mm.…”

Section: Introductionmentioning

confidence: 99%

“…Research on the dimension measurement of boxes in the field of computer vision technology has been published [3][4][5][6][7] and has achieved good results. In the present study, we used the line structured light vision to measure box dimensions.…”

Section: Introductionmentioning

confidence: 99%

Dimension Measurement and Key Point Detection of Boxes through Laser-Triangulation and Deep Learning-Based Techniques

et al. 2019

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Dimension measurement is of utmost importance in the logistics industry. This work studies a hand-held structured light vision system for boxes. This system measures dimension information through laser triangulation and deep learning using only two laser-box images from a camera and a cross-line laser projector. The structured edge maps of the boxes are detected by a novel end-to-end deep learning model based on a trimmed-holistically nested edge detection network. The precise geometry of the box is calculated by the 3D coordinates of the key points in the laser-box image through laser triangulation. An optimization method for effectively calibrating the system through the maximum likelihood estimation is then proposed. Results show that the proposed key point detection algorithm and the designed laser-vision-based visual system can locate and perform dimension measurement of measured boxes with high accuracy and reliability. The experimental outcomes show that the system is suitable for portable automatic box dimension online measurement.

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“…Range cameras find widespread use, for example in the field of robotics [1], in space [2,3], automation in *Correspondence: peter.fuersattel@fau.de 1 Pattern Recognition Lab, University of Erlangen -Nuremberg, Martensstrasse 3, Erlangen, Germany 2 Metrilus GmbH, Henkestrasse 91, Erlangen, Germany Full list of author information is available at the end of the article logistics [4] or in augmented reality devices like the Google Tango phones. The major problem with these sensors is their limited accuracy.…”

Section: Introductionmentioning

confidence: 99%

Accurate laser scanner to camera calibration with application to range sensor evaluation

Fuersattel

Plank

Maier

et al. 2017

IPSJ T Comput Vis Appl

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Multi-modal sensory data plays an important role in many computer vision and robotics tasks. One popular multi-modal pair is cameras and laser scanners. To overlay and jointly use the data from both modalities, it is necessary to calibrate the sensors, i.e., to obtain the spatial relation between the sensors. Computing such a calibration is challenging as both sensors provide quite different data: cameras yield color or brightness information, laser scanners yield 3-D points. However, several laser scanners additionally provide reflectances, which turn out to make calibration to a camera well feasible. To this end, we first estimate a rough alignment of the coordinate systems of both modalities. Then, we use the laser scanner reflectances to compute a virtual image of the scene. Stereo calibration on the virtual image and the camera image are then used to compute a refined, high-accuracy calibration. It is encouraging that the accuracies in our experiments are comparable to camera-camera stereo setups and outperform another of other target-based calibration approach. This shows that the proposed algorithm reliably integrates the point cloud with the intensity image. As an example application, we use the calibration results to obtain ground-truth distance images for range cameras. Furthermore, we utilize this data to investigate the accuracy of the Microsoft Kinect V2 time-of-flight and the Intel RealSense R200 structured light camera.

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Robust Estimation of Object Dimensions and External Defect Detection with a Low-Cost Sensor

Cited by 12 publications

References 23 publications

Portable System for Box Volume Measurement Based on Line-Structured Light Vision and Deep Learning

Portable System for Box Volume Measurement Based on Line-Structured Light Vision and Deep Learning

Dimension Measurement and Key Point Detection of Boxes through Laser-Triangulation and Deep Learning-Based Techniques

Accurate laser scanner to camera calibration with application to range sensor evaluation

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