نتایج جستجو برای: shape and texture features
تعداد نتایج: 16887710 فیلتر نتایج به سال:
Behavioral research has demonstrated that the shape and texture of single objects can be processed independently. Similarly, neuroimaging results have shown that an object's shape and texture are processed in distinct brain regions with shape in the lateral occipital area and texture in parahippocampal cortex. Meanwhile, objects are not always seen in isolation and are often grouped together as...
This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The...
Facial expression is one form of communication which being non-verbal in nature precedes verbal both origin and conception. Most the existing methods for Automatic Expression Recognition (AFER) are mainly focused on global feature extraction assuming that all facial regions contribute equal amount discriminative information to predict class. The detection localization have significant contribut...
This paper proposes a novel image retrieval algorithm using local color feature of image sub-block and global texture and shape features. Image sub-blocks are identified by partitioning the image into blocks. Color Texture and shape are the low level image descriptor in Content Based Image Retrieval. These low level image descriptors are used for image representation and retrieval in CBIR. In t...
This chapter reviews and discusses various aspects of texture analysis. The concentration is on the various methods of extracting textural features from images. The geometric, random field, fractal, and signal processing models of texture are presented. The major classes of texture processing problems such as segmentation, classification, and shape from texture are discussed. The possible appli...
Content Based Image Retrieval is a technique of automatic indexing and retrieving of images from a large data base. Visual features such as color, texture and shape are extracted to differentiate images in Content Based Image Retrieval (CBIR). Each of the features can be represented using one or more feature descriptors. These features descriptors combined with form feature vectors and are used...
In this paper, we present a face alignment system to deal with various poses and expressions. In addition to global shape model, we use component shape model such as mouth shape model, contour shape model in addition to global shape model to achieve more powerful representation for face components under complex pose and expression variations. Different from 1-D profile texture feature in classi...
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