Velocity and distance of neighbourhood sequences

Das et al. [2] defined the notion of periodic neighbourhood sequences. They also introduced a natural ordering relation for such sequences. Fazekas et al. [4] generalized the concept of neighbourhood sequences, by dropping periodicity. They also extended the ordering to these generalized neighbourhood sequences. The relation has some unpleasant properties (e.g., it is not a complete ordering). In certain applications it can be useful to compare any two neighbourhood sequences. For this purpose, in the present paper we introduce a norm-like concept, called velocity, for neighbourhood sequences. This concept is in very close connection with the natural ordering relation. We also define a metric for neighbourhood sequences, and investigate its properties

Approximation of the Euclidean distance by Chamfer distances

Chamfer distances play an important role in the theory of distance transforms. Though the determination of the exact Euclidean distance transform is also a well investigated area, the classical chamfering method based upon "small" neighborhoods still outperforms it e.g. in terms of computation time. In this paper we determine the best possible maximum relative error of chamfer distances under various boundary conditions. In each case some best approximating sequences are explicitly given. Further, because of possible practical interest, we give all best approximating sequences in case of small (i.e. 5x5 and 7x7) neighborhoods

Diszkrét módszerek a digitális képfeldolgozásban = Discrete methods in digital image processing

A beszámolási időszakban több területen végeztünk eredményes kutatómunkát. Szomszédsági szekvenciák. Korábbi eredményeket általánosítva jellemeztük a metrikus végperiodikus szekvenciákat. Meghatároztuk az euklideszi metrikát felülről legjobban közelítő oktagonális metrikát, választ adva Rosenfeld és Pfaltz egy régi problémájára. Leírtuk az oktagonális metrikus és általános szomszédsági szekvenciák több tulajdonságát. Algoritmust adtunk egy szekvencia által meghatározott legrövidebb út előállítására. Kidolgoztuk a szomszédsági szekvenciák különböző képfeldolgozási eljárásokban való alkalmazásának lehetőségeit. A háromszög-, hatszög-, BCC- és FCC- rácsokon is hasonló kutatásokat folytattunk. Diszkrét tomográfia. Megmutattuk, hogy egy tetszőleges digitális halmaz részhalmazait négy megfelelő irányban vett vonalösszegek egyértelműen meghatározzák. Vázkijelölés. Egy korábbi eredményünkre támaszkodva kidolgoztunk egy szekvencia alapú középtengely-transzformációt. Orvosi képfeldolgozás, virtuális műtéttervezés. Közreműködtünk egy klinikai diagnosztikát és műtétek tervezését segítő számítógépes rendszer kialakításában. Több eredményünket hatékonyan implementáltuk. Multi-modális ember-gép kapcsolat. Kidolgoztunk egy SVM-alapú módszert, mely az arcon az irodalmi öt osztályba sorolható érzelmeket legfeljebb 25%-os hibával felismeri. Célunk egy virtuális sakkozó létrehozása, aki képes az arci gesztusok felismerésére is. | We conducted research during the reported period in several topics. Neighborhood sequences. Generalizing previous results, we characterized the metrical ultimately periodic sequences. We determined the octagonal metrics best approximating the Euclidean one from above, answering an old problem of Rosenfeld and Pfaltz. We described several properties of octagonal metrical and general neighborhood sequences. We gave an algorithm to construct the shortest path corresponding to a sequence. We elaborated several applications of neighborhood sequences for various image processing methods. We did similar research for triangular-, hexagonal, BCC- and FCC-grids. Discrete tomography. We proved that the subsets of any digital set are uniquely determined by its line sums corresponding to four appropriately chosen directions. Skeletonization. Using one of our previous results, we worked out a sequence-based middle axis transformation. Medical image processing, virtual surgery. We took part in the construction of a software system helping clinical diagnostics and surgery planning. Many of our results have been efficiently implemented. Multi-modal human-machine interaction. Based on SVM algorithm we worked out a method to classify the emotions of the face into the five basic classes, with at most an error of 25%. Our purpose is to construct a virtual chess player that is able to recognize face gestures, too

A stochastic approach to improve macula detection in retinal images

In this paper, we present an approach to improve detectors used in medical image processing by fine-tuning their parameters for a certain dataset. The proposed algorithm uses a stochastic search algorithm to deal with large search spaces. We investigate the effectiveness of this approach by evaluating it on an actual clinical application. Namely, we present promising results with outperforming four state-of-the-art algorithms used for the detection of the center of the sharp vision (macula) in digital fundus images

Recognizing Typeset Documents using Walsh Transformation

In this paper we present an effective character recognition algorithm, which can be applied mainly to typeset documents. Our aim was to compose a character recognition algorithm, which can be used to recognize simple typeset documents in a fast and reliable way. To get a good result by this algorithm the input text document should contain characters from the same character set with a small number of symbols. This condition does not mean a strong restriction as the documents in practice usually have this property. The main character recognition part of the algorithm is based on the Walsh transformation, which gives a verbose description about the image, like the symmetrical relations, placement of the foreground and background pixels, and so on. That is why we tried to apply it to recognize characters, and the algorithm proved to be fairly efficient and reliable for simple documents, since the feature vectors extracted by Walsh transformation can be well distinguished. Moreover, our method had very good results in tolerating different types of noise corruption

Parameter Estimation of Drag Coefficient and Rolling Resistance of Vehicles Based on GPS Speed Data

In this paper, a parameter estimation method of the model-based design approach is applied to estimate the drag coefficient and the rolling resistance coefficient of a vehicle. In fact, a constant-force parameter (c_const) and a velocity-square-force parameter (c_square) are in the vehicle model, and these result in the sum force applied along the translational DOF that models the vehicle. It is only an assumption that the constant force is the rolling resistance and the force proportional to the square of the velocity is the drag force of the air. Only GPS speed data is used for the estimation process. The conclusion is that parameter estimation is a good alternative when expensive measurement devices are not available to measure the force losses separately and directly