Since 3D sensors became popular, imaged depth data are easier to obtain in the consumer sector. In applications such as defect localization on industrial objects or mass/volume estimation, precise depth data is important and, thus, benefits from the usage of multiple information sources. However, a combination…
In this work, a method for automatic analysis of natural aggregates using hyperspectral imaging and high-resolution RGB imaging combined with AI algorithms consisting of an intelligent deep-learning-based recognition routine in form of hybrid cascaded recognition routine, and a necessary demonstration…
This paper discusses the accuracy improvement of automatic analysis of construction and demolition waste (CDW) by using the combination of image analysis and spectral information. This means using the combination of methods of image processing, methods of spectral analysis and methods of supervised learning.…
In this paper a new method for the automatic visual inspection of metallic surfaces is proposed by using Convolutional Neural Networks (CNN). The different combinations of network parameters were developed and tested. The obtained results of CNN were analysed and compared with the results of our previous…
Quality assessment is an important step in production processes of metal parts. This step is required in order to check whether surface quality meets the requirements. Progress in the field of computing technologies and computer vision gives the possibility of visual surface quality control with industrial…
Braunschweig: International Measurement Confederation (IMEKO), 2016-11-30
A segmentation method of out-of-focus image regions for processed metal surfaces, based on focus textural features is proposed. Such regions contain small amount of useful information. The object of study is a metal surface, which has a cone shape. Some regions of images are blurred because the depth…
This paper discusses the possibility of automatic classifying of construction and demolition waste (CDW) by using methods of spectral analysis and supervised classifiers. The classification performances in colour images shown, that we have touse additional spectral information to solve the recognition…
Development of video, computing technologies and computer vision gives a possibility of automatic fire detection on video information. Under that project different algorithms was implemented to find more efficient way of fire detection. In that article colour based fire detection algorithm is described.…
The following paper deals with the classification of seeds and seed components of the South-American Incanut plant and the modification of a machine to handle this task. Initially the state of the art is being illustrated. The research was executed in Germany and with a relevant part in Peru and Ecuador.…
This paper discusses the possibility of the optical identification of recycled aggregates of construction and demolition waste (CDW) using methods of image processing, spectral analysis and machine learning. The classification performances in colour images shown, that we have to use other added spectral…
This paper discusses two analysis activities in the construction material industry, which could be solved by intelligent image processing algorithms. The first task is the optical identification of recycled aggregates of construction and demolition waste (CDW) as basis of an innovative sorting method…
Braunschweig: International Measurement Confederation (IMEKO), 2013-08
Natural products are exposed to various environmental
influences resulting in a high phenotypical variability. This
makes it very difficult to develop automatic recognition algorithms
in contrast to the recognition of manufactured products.
Recent developments in the field of computer science, especially
the…