Abstract: A camera device for reading optical codes is provided that has at least one first camera unit having a first camera controller and a first image sensor for recording image data from a first detection zone, that has second camera unit having a second camera controller and that has a second image sensor for recording image data from a second detection zone that overlaps at least partially with the first detection zone, and that has a common control unit, wherein the respective camera controller is configured to locate regions of interest having optical codes in the image data and to transmit the image data of the regions of interest to the common controller. In this respect, the common controller is configured to combine the image data in regions of interest recorded by more than one camera unit and to read an optical code in the region of interest therefrom.

Abstract: A method of locating code image zones in an output image of a code bearing object (14), wherein first candidates for code image zones are determined in a first segmentation process using a process of classical image processing without machine learning and second candidates for code image zones are determined in a second segmentation process using machine learning, with the first and second candidates being fused to locate the code image zones.

Abstract: A method is proposed of reading an optical code that encodes a message that has a character chain having a plurality of characters, said method comprising the steps: recording image data having the optical code; evaluating the image data with a reading of the optical code; comparing the read characters of the message with a scheme that contains a fixed character for at least one position of the message that is expected at this position in codes to be read; and recognizing an incorrectly read message and/or correcting the read message with reference to the comparison with the scheme. The scheme contains a variable character that is expected at this position in codes to be read for at least one position of the message, with a variable character being set to a partial range of the possible characters, but not to a fixed character.

Abstract: A method of automatically setting up a code reading device that has an image sensor and a control and evaluation unit, wherein an example image of an example object arranged in the field of view of the image sensor and having an example code is recorded by the image sensor and at least one recording parameter and/or at least one decoding parameter for the operation of the code reading device is set with reference to an evaluation of the example image. In this respect, further example images are generated from the example image by calculational variation and the at least one recording parameter and/or the at least one decoding parameter is/are set with reference to an evaluation of the further example images.

Abstract: A method of reading an optical code (20) is provided in which image data with the code (20) are recorded by an image sensor (24), a first processing unit (30) reads the image data from the image sensor (24) and generates metadata with respect to the image data and/or to the code (20) in the course of a pre-processing of the image data, and a second processing unit (32) reads the code (20) after the pre-processing by the first processing unit (30), The second processing unit (32) reads the code (20) solely from the metadata without making use of the image data.

Abstract: A method of determining the module size of an optical code (20) is specified in which image data having the code (20) are recorded and the module size is estimated from distances between light-dark transitions in the image data, At least one frequency distribution, in particular a histogram, is formed that indicates how often dark and/or light pixel sequences of a respective number occur along at least one line through the code (20) and the module size is estimated from the frequency distribution.

Abstract: A camera device having an image sensor for recording an image and having a control and evaluation unit configured to subdivide the image into first subregions, to find a second subregion in the image with structures of interest, and to carry out a brightness adjustment of the image, wherein the control and evaluation unit is further configured to determine a respective brightness distribution for the first subregions, to determine a selection of those first subregions that correspond to the second subregion, to generate a common brightness distribution of the second subregion from the brightness distributions of the first subregions of the selection, and to use the common brightness distribution to carry out the brightness adjustment for the second subregion.

Abstract: A method is proposed of reading an optical code that encodes a message that has a character chain having a plurality of characters, said method comprising the steps: recording image data having the optical code; evaluating the image data with a reading of the optical code; comparing the read characters of the message with a scheme that contains a fixed character for at least one position of the message that is expected at this position in codes to be read; and recognizing an incorrectly read message and/or correcting the read message with reference to the comparison with the scheme. The scheme contains a variable character that is expected at this position in codes to be read for at least one position of the message, with a variable character being set to a partial range of the possible characters, but not to a fixed character.

Abstract: A method of locating code image zones in an output image of a code bearing object (14), wherein first candidates for code image zones are determined in a first segmentation process using a process of classical image processing without machine learning and second candidates for code image zones are determined in a second segmentation process using machine learning, with the first and second candidates being fused to locate the code image zones.

Abstract: A method of automatically setting up a code reading device that has an image sensor and a control and evaluation unit, wherein an example image of an example object arranged in the field of view of the image sensor and having an example code is recorded by the image sensor and at least one recording parameter and/or at least one decoding parameter for the operation of the code reading device is set with reference to an evaluation of the example image. In this respect, further example images are generated from the example image by calculational variation and the at least one recording parameter and/or the at least one decoding parameter is/are set with reference to an evaluation of the further example images.

Abstract: A method for determining a module size of an optical code (20), wherein image data with the code (20) are detected, a brightness distribution is determined from the image data, and the module size is determined from the brightness distribution. The brightness distribution for example is a greyscale histogram.

Abstract: An optoelectronic code reader (10) having at least one light receiving element (24) for generating image data from reception light and an evaluation unit (26) with a classifier (30) being implemented in the evaluation unit (26) for assigning code information to code regions (20) of the image date, wherein the classifier (30) is configured for machine learning and is trained by means of supervised learning based on codes read by a classic decoder (28) which does not make use of methods of machine learning.

Abstract: A code reader for the reading of optical codes is provided that has an image sensor for the detection of image data with the code and that has a control and evaluation unit that is configured to read the code with at least one decoding method, wherein the control and evaluation unit is connected to a distance sensor that determines a distance value for the distance of the code. The control and evaluation unit is further configured for the purpose of setting at least one parameter and/or including at least one additional algorithm of the decoding method for the decoding method in dependence on the distance value.

Abstract: A code reader for the reading of optical codes is provided that has an image sensor for the detection of image data with the code and that has a control and evaluation unit that is configured to read the code with at least one decoding method, wherein the control and evaluation unit is connected to a distance sensor that determines a distance value for the distance of the code. The control and evaluation unit is further configured for the purpose of setting at least one parameter and/or including at least one additional algorithm of the decoding method for the decoding method in dependence on the distance value.

Abstract: A method for determining a module size of an optical code (20), wherein image data with the code (20) are detected, a brightness distribution is determined from the image data, and the module size is determined from the brightness distribution. The brightness distribution for example is a greyscale histogram.

Abstract: A method of reading an optical code (20) is provided that has a plurality of code words, wherein image data having the optical code (20) are recorded and evaluated to read out the code words, and wherein it is determined by a test process whether the code is read correctly. In this respect, a code word at at least one position of the code (20) is replaced with a code word known for this position in a pre-correction and the test process is carried out after the pre-correction.

Abstract: An optoelectronic code reader (10) having at least one light receiving element (24) for generating image data from reception light and an evaluation unit (26) with a classifier (30) being implemented in the evaluation unit (26) for assigning code information to code regions (20) of the image date, wherein the classifier (30) is configured for machine learning and is trained by means of supervised learning based on codes read by a classic decoder (28) which does not make use of methods of machine learning.

Abstract: A method of reading an optical code (20) is provided that has a plurality of code words, wherein image data having the optical code (20) are recorded and evaluated to read out the code words, and wherein it is determined by a test process whether the code is read correctly. In this respect, a code word at at least one position of the code (20) is replaced with a code word known for this position in a pre-correction and the test process is carried out after the pre-correction.

Abstract: A detection system for optical codes that are applied to an object that is conveyed through a reading field of a sensor of the detection system, wherein the detection system is configured to record a sequence of images from a respective part of the object which is present in the reading field at the respective time of recording of a respective image by means of the sensor, is characterized in that the detection system is further configured to determine a respective displacement vector between two respective consecutive images of the image sequence by means of the two respective consecutive images, wherein the respective displacement vector reflects how far an image region included in an image is displaced relative to a previous image, and with the image region also being present in the previous image.

Abstract: An optoelectronic device (10) is provided having an image sensor (20) for generating pixel images of a detection area (12) and a brightness correction unit (28) configured to modify brightness values of the pixels with a correction factor (Hmul) to obtain a more homogeneously illuminated image. A respective correction factor (Hmul) is calculated for individual pixels or groups of pixels from a perspective transformation (M) which converts geometries of an object plane (34) in the detection area (12) into geometries of the image plane (32).