Probabilistic framework for image understanding applications using Bayesian Networks

Machine learning algorithms have been successfully utilized in various systems/devices. They have the ability to improve the usability/quality of such systems in terms of intelligent user interface, fast performance, and more importantly, high accuracy. In this research, machine learning techniques are used in the field of image understanding, which is a common research area between image analysis and computer vision, to involve higher processing level of a target image to make sense of the scene captured in it. A general probabilistic framework for image understanding where topics associated with (i) collection of images to generate a comprehensive and valid database, (ii) generation of an unbiased ground-truth for the aforesaid database, (iii) selection of classification features and elimination of the redundant ones, and (iv) usage of such information to test a new sample set, are discussed. Two research projects have been developed as examples of the general image understanding framework; identification of region(s) of interest, and image segmentation evaluation. These techniques, in addition to others, are combined in an object-oriented rendering system for printing applications. The discussion included in this doctoral dissertation explores the means for developing such a system from an image understanding/ processing aspect. It is worth noticing that this work does not aim to develop a printing system. It is only proposed to add some essential features for current printing pipelines to achieve better visual quality while printing images/photos. Hence, we assume that image regions have been successfully extracted from the printed document. These images are used as input to the proposed object-oriented rendering algorithm where methodologies for color image segmentation, region-of-interest identification and semantic features extraction are employed. Probabilistic approaches based on Bayesian statistics have been utilized to develop the proposed image understanding techniques

An image system for CINDI

Content Based Image Retrieval (CBIR) becomes possible and necessary as computer graphics, machine learning, knowledgebase and database technologies mature. SHMM aims to be a web oriented image library with an automatic image addition and classification mechanism to support sample image based similarity search, and semantic description search as well as allowing the registered users to add image to the database. As a sample CBIR system, SHMMhas its feature extraction layer, which supports colour and texture feature extraction that generates a 16-dimensional vector value. Based on this vector, a 16-dimensional SR tree is constructed. Using the nearest neighbor search technology on the SR tree, similarity search is supported. With backend database support, semantic description search, which is based on the keyword of the semantic meaning of image, is also implemented in SHMM. When a new image is added to the system, SHMM will automatically scan its feature, suggest the semantic description based on the similarity search result in the library, and wait for the user's response. Image contributor can accept the system's suggestion or inform system administrator via email to create new semantic description category in the system. (Abstract shortened by UMI.

Implementasi Metode Kombinasi Histogram Of Oriented Gradients Dan Hirerarchical Centroid Untuk Sketch Based Image Retrieval

Teknik pencarian gambar yang saat ini umum digunakan masih berbasis teks atau text based search seperti pada mesin pencarian Google Image, Yahoo, dan lain sebagainnya. Namun metode ini masih kurang efektif karena nama dari sebuah file tidak dapat merepresentasikan isinya, oleh karena itu diperlukan pemilihan kata kunci yang benar-benar tepat agar hasil yang diinginkan dapat ditampilkan dengan baik. Salah satu teknik pencarian gambar yang saat ini sedang diteliti adalah Sketch-Based Image Retrieval (SBIR). Dengan teknik ini user dapat menginputkan sketsa gambar atau user dapat menggambarkan obyek pada area yang disediakan lalu sistem akan melakukan pencocokkan sketsa dengan database gambar. Untuk mengimplementasikan teknik ini digunakan metode kombinasi Histogram of Oriented Gradient dan Hierarchical Centroid. Tahapan implementasi teknik tersebut yaitu, yang pertama melakukan preprocessing pada gambar dengan cara mendeteksi tepi obyek lalu membuat citra menjadi hitam putih. Yang kedua melakukan ektraksi fitur menggunakan Histogram of Oriented Gradients dan Hierarchical Centroid dan menghasilkan fitur vektor. Yang terakhir menghitung jarak kedekatan antara gambar yang diuji dengan gambar yang terdapat dalam database menggunakan Euclidean Distance. Hasil Euclidean Distance kemudian diurutkan secara ascending dan dikembalikan sejumlah gambar yang jaraknya terdekat. Hasil temu kembali menghasilkan nilai Average Normalized Modified Retrieval Rank sebesar 0,35 dan nilai presisi dan recall sebesar 78 % dan akurasi sebesar 96%. ========== Technique that commonly used in search image is text based search as well as in the searching machine like Google image, Yahoo an so on. But this method is not really effective because name of an image can not represented the content, therefore it is necessary keyword selection that can displayed result properly. One of image search technique that currently being studied is Sketch Based Image Retrieval (SBIR). With this technique, user can input sketch image or user can sketch image in the area provided and then the system will match a sketch image with database image. To implement this technique used combination of method Histogram of Oriented Gradients and Hierarchical Centroid. First perform preprocessing on the image by detecting the edge of the object and make an image to black and white, Then exctrated feature using Histogram of Oriented Gradients and Hierarchical Centroid and generate vector features. Last, calculates the distance between test image and database image using euclidean distance and sort the result in ascending and retrieve a number of images that have high proximity. The result of the test of the system obtained 0,35 of Average Normalized Modified Retrieval Rank, precission and recall 78% and also accuracy 96%

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

<p>Abstract</p> <p>Background</p> <p>Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information.</p> <p>Results</p> <p>In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data.</p> <p>Conclusions</p> <p>Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.</p

Data Vaults: a Database Welcome to Scientific File Repositories

Efficient management and exploration of high-volume scientific file repositories have become pivotal for advancement in science. We propose to demonstrate the Data Vault, an extension of the database system architecture that transparently opens scientific file repositories for efficient in-database processing and exploration. The Data Vault facilitates science data analysis using high-level declarative languages, such as the traditional SQL and the novel array-oriented SciQL. Data of interest are loaded from the attached repository in a just-in-time manner without need for up-front data ingestion. The demo is built around concrete implementations of the Data Vault for two scientific use cases: seismic time series and Earth observation images. The seismic Data Vault uses the queries submitted by the audience to illustrate the internals of Data Vault functioning by revealing the mechanisms of dynamic query plan generation and on-demand external data ingestion. The image Data Vault shows an application view from the perspective of data mining researchers

Integrated CMS Website Implementation With The Codeigniter Framework

Content Management System (CMS) is a system or software in developing content. What is meant by content is all forms of digital information, in the form of image files, audio, video, text and other computer files. CMS makes it easy to create attractive website pages without having to understand how to create a website from scratch. Likewise, Lancang Kuning University has created an Integrated CMS website or integrated with faculty websites at Lancang Kuning University, by creating one database but the frontend and backend templates can be customized as desired. With this integrated website, it will make it easier for the main admin and faculty admin to maintain the website, including in its development. This website was built using the concept of Object Oriented and using a codeigniter framework.

A real-time distributed analysis automation for hurricane surface wind observations

From 1993 until 1999, the Hurricane Research Division of the National Oceanic and Atmospheric Administration (NOAA) produced real-time analyses of surface wind observations to help determine a storm\u27s wind intensity and extent. Limitations of the real-time analysis system included platform and filesystem dependency, lacking data integrity and feasibility for Internet deployment. In 2000, a new system was developed, built upon a Java prototype of a quality control graphical client interface for wind observations and an object-relational database. The objective was to integrate them in a distributed object approach with the legacy code responsible for the actual real-time wind analysis and image product generation. Common Object Request Broker Architecture (CORBA) was evaluated, but Java Remote Method Invocation (AMI) offered important advantages in terms of reuse and deployment. Even more substantial, though, were the efforts towards object-oriented redesign, implementation and testing of the quality control interface and its database performance interaction. As a result, a full-featured application can now be launched from the Web, potentially accessible by tropical cyclone forecast and warning centers worldwide

Similarity of Inference Face Matching On Angle Oriented Face Recognition

Face recognition is one of the wide applications of image processing technique. In this paper complete image of face recognition algorithm is proposed. In the prepared algorithm the local information is extracted using angle oriented discrete cosine transforms and invokes certain normalization techniques. To increase the Reliability of the Face detection process, neighborhood pixel information is incorporated into the proposed method. Discrete Cosine Transform (DCT) are renowned methods are implementing in the field of access control and security are utilizing the feature extraction capabilities. But these algorithms have certain limitations like poor discriminatory power and disability to handle large computational load. The face matching classification for the proposed system is done using various distance measure methods like Euclidean Distance, Manhattan Distance and Cosine Distance methods and the recognition rate were compared for different distance measures. The proposed method has been successfully tested on image database which is acquired under variable illumination and facial expressions. It is observed from the results that use of face matching like various method gives a recognition rate are high while comparing other methods. Also this study analyzes and compares the obtained results from the proposed Angle oriented face recognition with threshold based face detector to show the level of robustness using texture features in the proposed face detector. It was verified that a face recognition based on textual features can lead to an efficient and more reliable face detection method compared with KLT (Karhunen Loeve Transform), a threshold face detector. Keywords: Angle Oriented, Cosine Similarity, Discrete Cosine Transform, Euclidean Distance, Face Matching, Feature Extraction, Face Recognition, Image texture features

An eCommerce Development Case: Your Company\u27s eCommerce Web Site

This case provides a real-world semester long project-oriented case study for students enrolled in an electronic commerce course that has a significant development component. The case provides the technical framework in the form of functional requirements for students to design and build a fully functional transaction processing e-commerce Web site over the course of a semester based on the company, products and/or services, content, and graphic images they choose. The case is divided into three assignments. The first assignment is a basic e-commerce Web site that emphasizes site layout, navigation, text formatting, inserting graphics, and the content necessary to market products and services online. Additional complexity is added in the second assignment, an enhanced e-commerce Web site. In this assignment students will create their own graphics images, menus, and image maps, use JavaScript to create image rollovers and image swaps, dynamically generate Web pages based on the contents of a database, and use a form to send data to an email address. The third assignment is a full-fledged transaction processing e-commerce Web site with a virtual shopping cart and checkout processing procedures. The case can to be used in a course where the students have little or no prior programming or relational database experience. The case was written so that the creation of the student\u27s e-commerce Web site is not dependent upon the student\u27s e-commerce development software, graphics tool set, Web server, Web programming environment, or relational database management system. Teaching notes containing suggested instructions, possible development environments, Web server configurations hints, individual assignment objectives, and a sample solution to the final assignment are provided

Cluster Oriented Image Retrieval System with Context Based Color Feature Subspace Selection

This paper presents a cluster oriented image retrieval system with context recognition mechanism for selection subspaces of color features. Our idea to implement a context in the image retrieval system is how to recognize the most important features in the image search by connecting the user impression to the query. We apply a context recognition with Mathematical Model of Meaning (MMM) and then make a projection to the color features with a color impression metric. After a user gives a context, the MMM retrieves the highest correlated words to the context. These representative words are projected to the color impression metric to obtain the most significant colors for subspace feature selection. After applying subspace selection, the system then clusters the image database using Pillar-Kmeans algorithm. The centroids of clustering results are used for calculating the similarity measurements to the image query. We perform our proposed system for experimental purpose with the Ukiyo-e image datasets from Tokyo Metropolitan Library for representing the Japanese cultural image collections