Recent Patents on Computer Science - Volume 4, Issue 1, 2011

In image and video analysis, distance transformations (DT) are frequently used. They provide a distance image (DI) of background pixels to the nearest object pixel. DT touches upon the core of many applications; consequently, not only science but also industry has conducted a significant body of work in this field. However, in a vast majority of the cases this has not been published in major scientific outlets but has been filed as a patent application. This article provides a brief introduction into DT, including a specification of a few of the most prominent algorithms in the field. Next, a few interesting algorithms from the last decade are discussed. A benchmark including eight DT algorithms (i.e., city block, Danielsson's algorithm, chamfer 3-4, hexadecagonal region growing, a recent claimed true Euclidean DT, and three exact Euclidean DT) has been executed, which illustrates the intriguing complexity of DT in terms of precision and computational complexity. Subsequently, a selection of key patent applications are discussed that have emerged in this field, including their scientific merit and areas of application. Finally, this article's findings are summarized and discussed, with an emphasis on both the common ground of scientific articles and patent applications as well as the added value they can have to each other.

With the rapidly increasing availability of laser scanning data and the growing pressure to use it as the basis for computational models, there has been heightened interest in quickly, cost-effectively, and accurately processing the resulting point cloud data sets so that they are compatible for importation into computational models. This paper presents traditional strategies for solid model generation and examines in detail innovations and continuing limitations of recent patents, newly published research, and some currently available commercial programs for the transformation of laser scanning point cloud data into solid models appropriate for finite element method meshing. The focus is on building facades.

This paper presents a tractable and empirically-accurate algorithm, along with an integrated framework, realizing a mid-level visual process for pattern recognition. The algorithm and overall framework takes advantage of hypotheses provided by a high-level visual process, thereby, attempting to extract a region in an image based on these hypotheses. The main focus is to recognize analytical, as well as non-analytical objects from binary images. The novel approach is based on a study of the Hough Transform and its generalized version. To show the overall usefulness of the framework, an extensive series of experiments were performed. An analysis of absolute and percent error accuracy is presented, indicating the effectiveness of this work's approach. Finally, we review the main body of research in this area and identify the key patents that have emerged in this field.

With the development of high-throughput analysis, the growing data of gene expression profile can be provided. It is possible to predict gene function by analyzing sequence homology and co-expression relation of the known marker genes and novel genes. In order to improve the accuracy of prediction gene function, this paper attempts to predict gene function by using computational biology combined with sequence homology and gene co-expression. Given an amino acid encoded sequence of novel gene, its homologous and co-expressed genes which encode the protein having enzyme function, the following questions are often asked. Is the amino acid encoded sequence of novel gene an enzyme or non-enzyme? If it is, which main family class does it belong to? Or going further deeper, what about its sub-functional class? In this paper, the training dataset was used by Shen and Chou. By using amino acid composition, low-frequency power spectral density, increment of diversity values, dipeptide amino acid compositions and pseudo amino acid composition to express the information of sequence, a support vector machine (SVM) or increment of diversity (ID) for predicting enzyme function of novel genes is proposed. The biological functions of 25 novel genes have been obtained. The article presents some promising patents on predicting gene function by using computational biology combines with gene homology and co-expression.

Credit decision is one of the major businesses for banks, and it plays a vital role for a bank’s development. It is of vital importance to improve the identification accuracy of debtors' financial situations, though there are many tools for financial data analysis. Support vector machine (SVM), a technique of artificial intelligence, has a relatively high accuracy for solving binary classification problems with small samples. This paper used ST (Special Treatment) together with an improvement of long-term loans for two consecutive years and non-ST (never under special treatment) of Chinese listed companies as two classes of financial situations and employed financial indicators as variables to construct SVM models for banks' credit decision-making, along with the discussion of related recent patents. Our conclusion is that SVM has relatively higher classification accuracy than some other classifiers, including neural network, decision tree, and discriminant analysis. Therefore, application of SVM to bank credit decision-making is feasible and efficient. The review also discussed relevant patents.

Digital watermarking has become a hot research topic in recent years. The main aim of digital watermarking is to prevent unauthorized reproduction of digital data and to protect copyrights. Most of the research on digital watermarking deal with invisible and robust watermark. The techniques and algorithms proposed in literature for watermarking can be grouped into three classes: time domain, frequency domain and time-frequency domain. In this paper, we review some recent research and patents on digital watermarking in the three different domains published within the last three years with main focus on invisible robust watermarking.

One of the most important debates about symbolic entities is about its ontological status. In other words, their true nature. There are three knowledge domains, logic, mathematics and computer languages (algorithms), that share a common nature. From a conceptual analysis, we can justify that all three fields are logically equivalent and that the statements about one of them should be automatically extrapolated to other two. There is also a very important question regarding software-mathematical-logical objects: the object contains in itself the process by which it is possible, that is the diverse verification, justification or demonstration processes. Patents on these fields should be severely restricted by very special circumstances, but should be not so easy to obtain. Beyond the academic, industrial and social claims on authorship, abstract knowledge belongs to the human species, in the same way as DNA is the essence of our physical structure.

A novel design of molecular buffer for molecule storage and delivery using a PANDA ring resonator is proposed. The optical vortices can be generated and controlled to form the trapping tools in the same way as the optical tweezers. In theory, the trapping force is formed by the combination between the gradient field and scattering photons, which is reviewed. By using the intense optical vortices generated within the PANDA ring resonator, the required molecules can be trapped and moved (transported) dynamically within the wavelength router or network, in which the molecular buffer can be performed within the wavelength router before reaching the required destination. The advantage of the proposed system is that a transmitter and receiver can be formed within the same system, which is available for molecule storage and transportation. Relevant patents are also reviewed in this manuscript.

The patents annotated in this section have been selected from various patent databases. These recent patents are relevant to the articles published in this journal issue, categorized by different computation methods, bioinformatics, medical informatics, computer graphics, artificial intelligence, cybernetics, hardware architectures, software, theory and methods involved and related to computer science.