Pedro R. Fernández

Sensor Calibration Based on Incoherent Optical Fiber Bundles (IOFB) Used For Remote Image Transmission.

Image transmission using incoherent optical fiber bundles (IOFB) requires prior calibration to obtain the spatial in-out fiber correspondence in order to reconstruct the image captured by the pseudo-sensor. This information is recorded in a Look-Up Table (LUT), used later for reordering the fiber positions and reconstructing the original image. This paper presents a method based on line-scan to obtain the in-out correspondence. The results demonstrate that this technique yields a remarkable reduction in processing time and increased image quality by introducing a fiber detection algorithm, an intensity compensation process and finally, a single interpolation algorithm.

Sensor for Distance Estimation Using FFT of Images

In this paper, the problem of how to estimate the distance between an infrared emitter diode (IRED) and a camera from pixel grey-level intensities is examined from a practical standpoint. Magnitudes that affect grey level intensity were defined and related to the zero frequency component from the FFT image. A general model was also described and tested for distance estimation over the range from 420 to 800 cm using a differential methodology. Method accuracy is over 3%.

Location of Optical Fibers for the Calibration of Incoherent Optical Fiber Bundles for Image Transmission

Image transmission by incoherent optical fiber bundles (IOFBs) requires prior calibration to obtain the spatial in-out fiber correspondence to reconstruct the image captured by the pseudocamera. This information is recorded in a lookup table (LUT), which is later used for reordering the fiber positions and reconstructing the original image. This paper shows how to apply a fiber detection process to minimize the calibration time and improve the quality of the recovered image. Two different fiber detection methods were developed. The former uses the circular Hough transform algorithm based on the image gradient. The second algorithm combines a number of morphological transformations with distance transform. The results demonstrate that this technique provides a remarkable reduction in the processing time while improving fiber detection accuracy.

Calibration of Incoherent Optical Fiber Bundles for Image Transmission. Fibers Detection Process

Image transmission by incoherent optical fibers bundles requires a previous calibration to obtain the fibers spatial in-out correspondence in order to reconstruct at the output side an image presented on the input of the system. This information is recorded in a look-up table for later reordering of the fibers positions and reconstructs the original image. This paper shows how to minimize calibration time and improve the quality of the recovered image, by using a fibers detection process reducing the number of points to take into account in the calibration process. There is, also, an improvement in the quality of the recovered image compared with others techniques. In this paper two detection methods of circular patterns have been applied to a fiber bundle image captured by a CMOS sensor. The former utilizes the algorithm of circular Hough transform based on the gradient field of the image. A second one is introduced as a new hybrid algorithm that mixes some morphological transformations and distance transform. The results demonstrate that this technique offers a remarkable reduction of processing time and good detection.

A Focusing Method in the Calibration Process of Image Sensors Based on IOFBs

A focusing procedure in the calibration process of image sensors based on Incoherent Optical Fiber Bundles (IOFBs) is described using the information extracted from fibers. These procedures differ from any other currently known focusing method due to the non spatial in-out correspondence between fibers, which produces a natural codification of the image to transmit. Focus measuring is essential prior to carrying out calibration in order to guarantee accurate processing and decoding. Four algorithms have been developed to estimate the focus measure; two methods based on mean grey level, and the other two based on variance. In this paper, a few simple focus measures are defined and compared. Some experimental results referred to the focus measure and the accuracy of the developed methods are discussed in order to demonstrate its effectiveness.

Simplified Method for Radiometric Calibration of an Array Camera

Radiometric calibration of a CCD camera is a first step when quantitative measurements for pixels values will be performed in order to extract scene characteristics. Usually, the radiometric behaviour of the camera can be modelled with a polynomial function obtained from a multi- image calibration method, which analyses several pictures taken with different exposition times. In this work, a simplification of a multi-images calibration method is proposed. The method is based on the comparison of grey values of two images only, showing that obtained results are comparables to the polynomic multi-image method. The proposed method was tested with the same images used for multi-image calibration method. Exposition times were estimated without an iterative scheme. Also a method and results for distance estimation, using inverse radiometric response function, are showed in this paper.

Differential Binary Encoding Method for Calibrating Image Sensors Based on IOFBs

Image transmission using incoherent optical fiber bundles (IOFBs) requires prior calibration to obtain the spatial in-out fiber correspondence necessary to reconstruct the image captured by the pseudo-sensor. This information is recorded in a Look-Up Table called the Reconstruction Table (RT), used later for reordering the fiber positions and reconstructing the original image. This paper presents a very fast method based on image-scanning using spaces encoded by a weighted binary code to obtain the in-out correspondence. The results demonstrate that this technique yields a remarkable reduction in processing time and the image reconstruction quality is very good compared to previous techniques based on spot or line scanning, for example.

Sensor for Distance Measurement Using Pixel Grey-Level Information

An alternative method for distance measurement is presented, based on a radiometric approach to the image formation process. The proposed methodology uses images from an infrared emitting diode (IRED) to estimate the distance between the camera and the IRED. Camera output grey-level intensities are a function of the accumulated image irradiance, which is also related by inverse distance square law to the distance between the camera and the IRED. Analyzing camera-IRED distance, magnitudes that affected image grey-level intensities, and therefore accumulated image irradiance, were integrated into a differential model which was calibrated and used for distance estimation over a 200 to 600 cm range. In a preliminary model, the camera and the emitter were aligned.

Improving the Calibration of Image Sensors Based on IOFBs, Using Differential Gray-Code Space Encoding

This paper presents a fast calibration method to determine the transfer function for spatial correspondences in image transmission devices with Incoherent Optical Fiber Bundles (IOFBs), by performing a scan of the input, using differential patterns generated from a Gray code (Differential Gray-Code Space Encoding, DGSE). The results demonstrate that this technique provides a noticeable reduction in processing time and better quality of the reconstructed image compared to other, previously employed techniques, such as point or fringe scanning, or even other known space encoding techniques.

Using the Standard Deviation of a Region of Interest in an Image to Estimate Camera to Emitter Distance

In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information.