The 3D-DCT transform: didactic experiment and possible useful tool

This article is about an image transform called 3D-DCT, or three-dimensional discrete cosine transform. This is an extension of the well-known 1D and 2D-DCT, which is extensively used, mostly in multimedia coding. A modification of 1D-DCT (MDCT) is used in audio coding, whereas 2D-DCT is the key concept for JPEG standard (still image coding) and also for very popular video coding standards: MPEG-1 and 2, H.261 & H.263. Other, more modern methods like MPEG-4/H.264 and the newest MPEG-H/H.265 use a modified version of 2D-DCT. Nevertheless, 3D-DCT is less known. In this work, a simple implementation for 3D-DCT is constructed and some applications are explored. This is designed as a material for class work but, as it will be shown in this paper, some practical applications can be interesting. 3D-DCT can be applied for creating a video coder much simpler than those following MPEG-x/H.26x and with only slightly less performance. 3D-DCT has also been tested for 3D medical imaging (CT studies) coding, yielding very interesting results.

Computer Vision Methods for Automating Turbot Fish Cutting

This paper is about the design of an automated machine to cut turbot fish specimens. Machine vision is a key part of this project as it is used to compute a cutting curve for the specimen head. This task is impossible to be carried out by mechanical means. Machine vision is used to detect head boundary and a robot is used to cut the head. Binarization and mathematical morphology are used to detect fish boundary and this boundary is subsequently analyzed (using Hough transform and convex hull) to detect key points and thus defining the cutting curve. Afterwards, mechanical systems are used to slice fish to get an easy presentation for end consumer (as fish fillets than can be easily marketed and consumed).

Simple Method for Perfect Reconstruction QMF Filter Design

The purpose of this work is the design of FIR QMF (Quadrature Mirror Filters) filters of perfect reconstruction and odd number of coefficients (even order). By design, these filters will have linear phase and integer delay. These filter pairs have many applications in wavelet transforms and other multi-frequency decompositions. Perfect reconstruction filters have been studied from long time ago but we still found publications about them.

Automatic Census of Mussel Platforms Using Sentinel 2 Images

Mussel platforms are big floating structures made of wood (size is normally about 20x20 meters or even a bit larger) that are used for aquaculture, id EST: growing mussels in appropriate marine waters. These structures are very typical in Galician estuaries. Being interesting to produce a periodic census of these structures that would allow knowing their number and positions, as well as changes on those parameters; Satellites that obtain periodic images for earth observation are a natural election for this issue. This paper describes a preliminary application able to construct automatically such a census using Sentinel 2 images (Copernicus Project). Copernicus satellites are run by European Space Agency (ESA) and the produced images are freely distributed on the internet. Sentinel 2 images have thirteen frequency bands and are updated each five days. In our application, we use remote sensing normalized (differential) indexes and artificial Neural Networks applied to multiband data. Different methods are described and tested. Finally, results are presented.

PRNU Based Source Camera Identification for Webcam and Smartphone Videos

This communication is about an application of image forensics where we use camera sensor fingerprints to identify source camera (SCI: Source Camera Identification) in webcam/smartphone videos. Sensor or camera fingerprints are based on computing the intrinsic noise that is always present in this kind of sensors due to manufacturing imperfections. This is an unavoidable characteristic that links each sensor with its noise pattern. PRNU (Photo Response Non-Uniformity) has become the default technique to compute a camera fingerprint. There are many applications nowadays dealing with PRNU patterns for camera identification using still images. In this work we focus on video, first on webcam video and afterwards on smartphone video. Webcams and smartphones are the most used video cameras nowadays. Three possible methods for SCI are implemented and assessed in this work.