Generation of differential topographic images for surface inspection of long products

delaCalle, Francisco J.; García, Daniel; Usamentiaga, Rubén

doi:10.1007/s11554-018-0844-2

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…The acquisition procedure and the representation is studied in detail in [18]. As an example, in Figure 3 a flat steel surface is shown with the acquisition of one defective profile, its registration and the representation of the surface in the original gray-scale images and another format using heat-map colors.…”

Section: Representationmentioning

confidence: 99%

“…In order to check the viability of using the international standard value and to look for the value that gives the best results, a study of the threshold value is performed using the values in the interval [0.15, 2]. The value 0.15 is selected as the starting point because the noise introduced by the sensors is approximately this value [18].…”

Section: Segmentation Configurationmentioning

confidence: 99%

“…Once the surface is acquired, there are two approaches depending on the application: compare the whole surface with the final desired product or compare each profile with a section of the desired product. A long product is defined by its cross-section so each acquired profile can be compared with the cross-section model of the desired product to calculate the differences [18]. When the piece is not defined by a single cross-section, the whole surface must be compared at once, as in the case of circuit boards.…”

Section: Introductionmentioning

confidence: 99%

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Surface Defect System for Long Product Manufacturing Using Differential Topographic Images

Herrero

García

Usamentiaga

2020

Sensors

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Current industrial products must meet quality requirements defined by international standards. Most commercial surface inspection systems give qualitative detections after a long, cumbersome and very expensive configuration process made by the seller company. In this paper, a new surface defect detection method is proposed based on 3D laser reconstruction. The method compares the long products, scan by scan, with their desired shape and produces differential topographic images of the surface at very high speeds. This work proposes a novel method where the values of the pixels in the images have a direct translation to real-world dimensions, which enables a detection based on the tolerances defined by international standards. These images are processed using computer vision techniques to detect defects and filter erroneous detections using both statistical distributions and a multilayer perceptron. Moreover, a systematic configuration procedure is proposed that is repeatable and can be performed by the manufacturer. The method has been tested using train track rails, which reports better results than two photometric systems including one commercial system, in both defect detection and erroneous detection rate. The method has been validated using a surface inspection rail pattern showing excellent performance.

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Section: Representationmentioning

confidence: 99%

Section: Segmentation Configurationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Surface Defect System for Long Product Manufacturing Using Differential Topographic Images

Herrero

García

Usamentiaga

2020

Sensors

Self Cite

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Hierarchical registration method for surface quality inspection of long products

et al. 2023

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Manufacturing industry often uses 3D scanning technologies to inspect their products. Some of these techniques produce a point cloud that represent a section of the manufactured product. The clouds must be aligned to the model of the product in order to check its quality. Current registration methods are usually affected by dimensional problems or volumetric anomalies. This paper proposes a new method for the registration process aligning the cloud to the model in several steps. The first step is the state-of-the-art method. The second step uses the information acquired in the first one to perform a fine registration in order to not being affected by dimensional defects or little miss alignments in the previous step providing a huge improvement in the measurement of surface defects. In this paper, several techniques are proposed in order to provide a set of tools that the final users can tune to fit their needs. The whole procedure of registration can be run in real-time conditions using the sampling and caching strategies proposed. The methods proposed are tested over more than 10,000 profiles of a rail proving they successfully align the cloud and the model providing better results in the measurement of surface defects.

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Real-time filtering on parallel SIMD architectures for automated quality inspection

Usamentiaga

2020

J Real-Time Image Proc

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Generation of differential topographic images for surface inspection of long products

Cited by 4 publications

References 15 publications

Surface Defect System for Long Product Manufacturing Using Differential Topographic Images

Surface Defect System for Long Product Manufacturing Using Differential Topographic Images

Hierarchical registration method for surface quality inspection of long products

Real-time filtering on parallel SIMD architectures for automated quality inspection

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