Texture analysis plays an increasingly important role in computer vision. Since the textural properties of images appear to carry useful information for discrimination purposes, it is important to develop significant features for texture. Various texture feature extraction methods include those based on gray-level values, transforms, auto correlation etc. We have chosen the Gray Level Co occurr...

In recent decades, plastic-mulched farmland has expanded rapidly in China as well as in the rest of the world because it results in marked increases of crop production. However, plastic-mulched farmland significantly influences the environment and has so far been inadequately investigated. Accurately monitoring and mapping plastic-mulched farmland is crucial for agricultural production, environ...

This paper proposes segmentation of MRI brain tumor using cellular automata and classification of tumors using Gray level Co-occurrence matrix features and artificial neural network. In this technique, cellular automata (CA) based seeded tumor segmentation method on magnetic resonance (MR) images, which uses volume of interest (VOI) and seed selection. Seed based segmentation is performed in th...

Image segmentation is a key step of oil spills detection in SAR images. For the problem that the traditional multi-spectral clustering algorithm with the features extraction by GLCM (Gray-Level Co-occurrence Matrix) has such limitations as direction sensitivities and difficulties in selecting the best feature combination etc., this paper proposes a multi-scale segmentation method of oil spills ...

ion In this paper, we describe our first participation for the semantic indexing task at TRECVID 2010 [1]. We focus on extraction multiple low-level feature sets and a fusion method. In our system, six features are extracted for all the predefined concepts from the keyframes, including global features (RGB color histogram, HSV color histogram, edge histogram, Grey Level Co-occurrence Matrix, GI...

The developments of content based image retrieval (CBIR) systems used for image archiving are continued and one of the important research topics. Although some studies have been presented general image achieving, proposed CBIR systems for archiving of medical images are not very efficient. In presented study, it is examined the retrieval efficiency rate of spatial methods used for feature extra...

This paper presents 15 texture features based on GLCM (Gray-Level Co-occurrence Matrix) and GLRLM (Gray-Level Run-Length Matrix) to be used in an automatic computer system for breast cancer diagnosis. The task of the system is to distinguish benign from malignant tumors based on analysis of fine needle biopsy microscopic images. The features were tested whether they provide important diagnostic...

Keyword Down syndrome, Trisomy, Nuchal Translucency, Chromosomal Abnormalities, Gray Level Cooccurrence Matrix(GLCM), Support Vector Machine (SVM) Down syndrome or Trisomy 21 is a genetic disorder which causes mental disability to the baby during the gestation period. Ultrasound scan, a noninvasive test which includes ultrasound fetal image scan for the Nuchal Translucency measurement (NT). Thi...

In this paper a comparative study has been made regarding certain methods of image processing by the texture characteristic, to find the optimum method for detecting color texture. The study is based on the experiments. There are two main points: the quality of the detection and the response time. For the experiments have been used the co-occurrence matrix and the iso-segments matrix of the gra...

Land surface water mapping is one of the most basic classification tasks to distinguish water bodies from dry land surfaces. In this paper, a water mapping method was proposed based on multi-scale level sets and a visual saliency model (MLSVS), to overcome the lack of an operational solution for automatically, rapidly and reliably extracting water from large-area and fine spatial resolution Syn...