In order to solve the problem of forced landing in emergency for Unmanned Aerial Vehicles (UAVs), a multiinformation based algorithm for selecting forced landing area by step is proposed. In order to extract the slowly varying edges and weak edges in an aerial image, this algorithm adopted improved edge detection method to detect landing area without obstacles. To select the detected safe areas...

Outdoor scene analysis is a complex problem for both image processing and pattern recognition domains. There are two methods of segmenting images to look for objects in an image, block-based and region-based. Region-based method can provide some useful information about objects even though segmentation may not be perfect. There are three phases in this system: segmentation, features extraction ...

The image processing is an interesting and challenging field now a days and medical image processing plays a major role in it. The medical images are used to analysis the diseases like brain tumor, cancer, diabetes, etc. The brain tumor is one of the dangerous diseases where many people suffer from this disease. Image segmentation is used to take out the suspicious parts from medical images lik...

As we know, feature extraction has an important role in crowd density estimation. In our paper, we introduce a new texture feature called Tamura, which is usually used in image retrieval algorithms. On the other hand, the time consuming is another issue that must be considered, especially for the real-time application of the crowd density estimation. In most methods, multiple features with high...

Diffusion Tensor Magnetic Resonance Imaging (DTMRI) has proved useful for microstructure characterization of the brain. This technique also helps determining complex connectivity of fiber tracts. The brain white matter (BMW) changes with respect to age and corresponding appearance of white-matter lesions among the brain’s message-carrying axons affects cognitive functions in old age. In this pa...

In this paper, we propose a new method for detecting shot boundaries in video sequences by performing Hilbert transform and extracting feature vectors from Gray Level Co-occurrence Matrix (GLCM). The proposed method is capable of detecting both abrupt and gradual transitions such as dissolves, fades and wipes in the video sequences. The derived features on processing through Kernel k-means clus...

Segmentation of lung anatomical parts like fissures and bronchopulmonary segments are of clinical importance in interpreting and assessing the pathologies present in the lungs. Segmentation of fissures still remains a challenging task as the selection of the segmentation algorithm decides the accuracy of the fissure segmentation. We conducted experiments on the existing segmentation methods and...

Automated and accurate classification of brain MRI is such important that leads us to present a new robust classification technique for analyzing magnetic response images. The proposed method consists of three stages, namely, feature extraction, dimensionality reduction, and classification. We use gray level co-occurrence matrix (GLCM) to extract features from brain MRI and for selecting the be...

In this paper, the classification of Brain Magnetic Resonance Images (MRI) and Liver Computed Tomography (CT) images has been analysed using supervised technique. The proposed method includes four stages pre-processing, fuzzy clustering, feature extraction and classification. For extracting the features Gray Level Co-occurrence Matrix (GLCM) method has been used. The main features regarding sha...

This study proposes a novel method for multichannel image gray level co-occurrence matrix (GLCM) texture representation. It is well known that the standard procedure for the automatic extraction of GLCM textures is based on a mono-spectral image. In real applications, however, the GLCM texture feature extraction always refers to multi/hyperspectral images. The widely used strategy to deal with ...