Real-Time Wheel Detection and Rim Classification in Automotive Production

This paper proposes a novel approach to real-time automatic rim detection, classification, and inspection by combining traditional computer vision and deep learning techniques. At the end of every automotive assembly line, a quality control process is carried out to identify any potential defects in the produced cars. Common yet hazardous defects are related, for example, to incorrectly mounted rims. Routine inspections are mostly conducted by human workers that are negatively affected by factors such as fatigue or distraction. We have designed a new prototype to validate whether all four wheels on a single car match in size and type. Additionally, we present three comprehensive open-source databases, CWD1500, WHEEL22, and RB600, for wheel, rim, and bolt detection, as well as rim classification, which are free-to-use for scientific purposes.Comment: 5 pages, 7 figures, 3 table

Two Methods for Comparing Different Views of theSameObject

The viewing hemisphere of a 3-dimensional object can be partitioned into areas of similar views, termed view bubbles. We compare two procedures of generating view bubbles: tracking of object features, i.e., Gabor wavelet responses, by utilizing the continuity of successive views and matching of features in different views, which are assumed to be independent. Both procedures proved to be appropriate to detect canonical views. We found no difference concerning the size of the view bubbles, but tracking provides more precise correspondences than matching. Tracking is more appropriate for recognizing changes of features, whereas matching is more suitable if features of the same appearance are to be found

Estimation of Camera Planar Motion from Blurred Images

The topic of the paper is to estimate parameters of the camera motion using images taken at initial and current positions of the camera. An original method handling defocused images or images blurred in other ways is proposed. The method is based on registering the images by means of detected control points (CPs) and so-called combined invariants. These features are invariant both to rigid-body transform and to blurring caused by convolution with an arbitrary centrosymetric point-spread function (PSF). Thanks to this, the camera position can be estimated directly from defocused images without any deblurring

Moment Forms Invariant to Rotation and Blur in Arbitrary Number of Dimensions

We present the construction of combined blur and rotation moment invariants in arbitrary number of dimensions. Moment invariants to convolution with an arbitrary centrosymmetric filter are derived first, and then their rotationally invariant forms are found by means of group representation theory to achieve the desired combined invariance. Several examples of the invariants are calculated explicitly to illustrate the proposed procedure. Their invariance, robustness, and capability of using in template matching and in image registration are demonstrated on 3D MRI data and 2D indoor images

How to measure the pose robustness of object views

The viewing hemisphere of a three-dimensional object can be partitioned into areas of similar views, which provide pose robustness. We compare two procedures for measuring the robustness of views to pose variation: tracking of object features, i.e. Gabor wavelet responses, by utilizing the continuity of successive views and matching of features in different views, which are assumed to be independent. Both procedures proved to be appropriate to detect canonical views. We found no difference concerning the size of the view bubbles, but tracking provides more precise correspondences than matching. Tracking is more appropriate for recognizing changes of features, whereas matching is more suitable if features of the same appearance are to be found. q 2002 Elsevier Science B.V. All rights reserved. Keywords: Three-dimensional object perception; Pose robustness; Matching/tracking object features; Canonical views 1. Subject of investigation Many models have been proposed for three-dimensional object perception. Besides volume-based object representations, which seem to be very economical but often require the interaction from a user to acquire them, as for example, described in Ref. [1], many computational models combine two-dimensional views into the equivalent of a three-dimensiona

Application of Image Processing for the Conservation of the Medieval Mosaic

We present an application of digital image processing for the analysis of the medieval mosaic conservation. The reconstructed art piece was the "The Last Judgement" mosaic, situated on the wall of the St. Vitus cathedral in Prague, Czech Republic. The historical photograph of the mosaic from the century was compared with the photograph of the current state. The images were firstly preprocessed to increase their quality (noise reduction, deblurring). In the second stage, geometrical differences between images were removed by means of image registration techniques. Finally, differences of the current and historical photographs were identified

A new wavelet-based measure of image focus

We present a new measure of image focus. It is based on wavelet transform of the image and is defined as a ratio of high-passbgh and low-passbwnorms