Object classification in 3-D images using alpha-trimmed mean radial basis function network
نویسندگان
چکیده
منابع مشابه
Object classification in 3-D images using alpha-trimmed mean radial basis function network
We propose a pattern classification based approach for simultaneous three-dimensional (3-D) object modeling and segmentation in image volumes. The 3-D objects are described as a set of overlapping ellipsoids. The segmentation relies on the geometrical model and graylevel statistics. The characteristic parameters of the ellipsoids and of the graylevel statistics are embedded in a radial basis fu...
متن کامل3-D Visual Object Classification with Hierarchical Radial Basis Function Networks
In this chapter we present a 3-D visual object recognition system for an autonomous mobile robot. This object recognition system performs the following three tasks: Object localisation in the camera images, feature extraction, and classification of the extracted feature vectors with hierarchical radial basis function (RBF) networks.
متن کاملClassification of Skin Cancers using Radial basis Function Network
This paper suggests a model for classifying skin lesions into benign and malignant melanoma using radial basis function network (RBFN). The model initially converts the color image into gray image and then applies Median filter for removing thin hairs and other noises. It then segments the cancerous region through segmentation and then extracts features that represent the characteristics of the...
متن کاملPolarimetric SAR Image Classification Using Radial Basis Function Neural Network
This paper presents a robust radial basis function (RBF) network based classifier for polarimetric synthetic aperture radar (SAR) images. The proposed feature extraction process utilizes the covariance matrix, the gray level co-occurrence matrix (GLCM) based texture features, and the backscattering power (Span) combined with the H/α/A decomposition, which are projected onto a lower dimensional ...
متن کاملFast Voltage and Power Flow Contingency Ranking Using Enhanced Radial Basis Function Neural Network
Deregulation of power system in recent years has changed static security assessment to the major concerns for which fast and accurate evaluation methodology is needed. Contingencies related to voltage violations and power line overloading have been responsible for power system collapse. This paper presents an enhanced radial basis function neural network (RBFNN) approach for on-line ranking of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Image Processing
سال: 1999
ISSN: 1057-7149
DOI: 10.1109/83.806620