Vision-Based Spatter Classification for Contaminant Detection
نویسندگان
چکیده
This paper presents a new method for measuring and classifying spatter in gas metal arc welding (GMAW) by optical monitoring of the weld pool and surrounding area via a high-frame-rate camera. Image processing and tracking algorithms are described that extract and classify individual spatter events from raw camera images. This new sensor is then used to investigate the relationship between workpiece contamination and weld spatter.
منابع مشابه
Spatter Tracking in Laser Machining
In laser drilling, an assist gas is often used to remove material from the drilling point. In order to design assist gas nozzles to minimize spatter formation, measurements of spatter trajectories are required. We apply computer vision methods to measure the 3D trajectories of spatter particles in a laser cutting event using a stereo camera configuration. We also propose a novel method for cali...
متن کاملContamination Resulting From Aerosolized Fluid During Laparoscopic Surgery
BACKGROUND AND OBJECTIVES Aerosolized droplets of blood can travel considerable distances on release of intra-abdominal pressure during laparoscopic surgery. This creates an environmental hazard for members of the surgical team. This study describes and provides a method of measurement of aerosolized blood contamination during evacuation of the pneumoperitoneum in laparoscopic surgery. METHOD...
متن کاملIdentification of Houseplants Using Neuro-vision Based Multi-stage Classification System
In this paper, we present a machine vision system that was developed on the basis of neural networks to identify twelve houseplants. Image processing system was used to extract 41 features of color, texture and shape from the images taken from front and back of the leaves. The features were fed into the neural network system as the recognition criteria and inputs. Multilayer perceptron (MLP) ne...
متن کاملSUBCLASS FUZZY-SVM CLASSIFIER AS AN EFFICIENT METHOD TO ENHANCE THE MASS DETECTION IN MAMMOGRAMS
This paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. In this method, mammograms are segmented into regions of interest (ROI) in order to extract features including geometrical and contourlet coefficients. The extracted features benefit from...
متن کاملFacial Expression Recognition Based on Structural Changes in Facial Skin
Facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. In recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. As machine vision and artificial intelligence advan...
متن کامل