Accurate detection of weeds in farmland can help reduce pesticide use and protect the agricultural environment. To develop intelligent equipment for weed detection, this study used an imaging spectrometer system, which supports micro-scale plant feature analysis by acquiring high-resolution hyper spectral images of corn and a number of weed species in the laboratory. For the analysis, the objec...

Feature extraction is a significant procedure for target recognition and classification of remotely sensed images. In this paper, the previous feature extraction methods were considered to consist of three layers: the abstract layer, the methodology layer and the feature layer. A new feature extraction approach based on the shape adaptive neighborhood (SAN) in the abstract layer was proposed. F...

The correspondence problem in computer vision is basically a matching task between two or more sets of features. In this paper, we introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. The representation consists of two image measurements made at the feature points: shape and texture. Fea...

The present paper derived a new texture classification tactic using textons and rough sets. Texton is a statistical approach used to analyze the texture of an image. Textures will be developed only if the side elements lie within the contiguity. Texton Image has the discrimination power of color, texture and shape features. In the proposed tactic texton using rough texture spectrum and color fe...

We present an evaluation and comparison of the performance of four di5erent texture and shape feature extraction methods for classi(cation of benign and malignant microcalci(cations in mammograms. For 103 regions containing microcalci(cation clusters, texture and shape features were extracted using four approaches: conventional shape quanti(ers; co-occurrence-based method of Haralick; wavelet t...

In this work, a novel facial feature extraction method is proposed for automatic facial expressions recognition, which detecting local texture information, global texture information and shape information of the face automatically to form the facial features. First, Active Appearance Model (AAM) is used to locate facial feature points automatically. Then, the local texture information in these ...