Visibility Simulation Technique for Support of Visual Recognition of the Landform Features

نویسنده

  • Tomaž Podobnikar
چکیده

Novel technique for enhanced visual recognition of the landform features developed by spatial analysis on the digital terrain model (DTM) is proposed. The approach called “visibility simulation technique” is consisted form the following steps: (1) visibility calculation, (2) altering an azimuth and zenith angle (following the proposed algorithm), (3) generating continuous surfaces that indicate upper/lower views and relative relief, (4) visual recognition of morphological features by thematic and general cartography, as possible input for further modelling and phenomena detection. Modelling parameters are highly independent on the landform morphology where only the parameter of zenith angle needs some minor adjustments. An interesting application is generation of a comprehensive relative relief. An important auxiliary result considers improving of the DTM quality. The proposed technique was tested on the morphologically various terrains of Mars and demonstrated using a DTM produced from HRSC images of the Mars Express mission.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A COMPARATIVE ANALYSIS OF WAVELET-BASED FEMG SIGNAL DENOISING WITH THRESHOLD FUNCTIONS AND FACIAL EXPRESSION CLASSIFICATION USING SVM AND LSSVM

This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...

متن کامل

Evaluation and Ranking of Discrete Simulation Tools

In studying through simulation, choosing an appropriate tool/language would be a difficult task because many of them are available. On the other hand, few research works focus on evaluation of simulation tools/languages and their comparison. This paper makes a couple of evaluations and ranks more than fifty simulation tools that are currently available. The first evaluation and ranking is in th...

متن کامل

Facial expression recognition based on Local Binary Patterns

Classical LBP such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. In this paper, we introduce an improved LBP algorithm to solve these problems that utilizes Fast PCA algorithm for reduction of vector dimensions of extracted features. In other words, proffer method (Fast PCA+LBP) is an improved LBP algorithm that is extracted ...

متن کامل

Recognition of Visual Events using Spatio-Temporal Information of the Video Signal

Recognition of visual events as a video analysis task has become popular in machine learning community. While the traditional approaches for detection of video events have been used for a long time, the recently evolved deep learning based methods have revolutionized this area. They have enabled event recognition systems to achieve detection rates which were not reachable by traditional approac...

متن کامل

Face Recognition using Eigenfaces , PCA and Supprot Vector Machines

This paper is based on a combination of the principal component analysis (PCA), eigenface and support vector machines. Using N-fold method and with respect to the value of N, any person’s face images are divided into two sections. As a result, vectors of training features and test features are obtain ed. Classification precision and accuracy was examined with three different types of kernel and...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009