In this study, prior to the launch of compact advanced satellite 500 (CAS500-4), which is an agriculture and forestry satellite, nine major tree species were classified using multi-temporally integrated imageries based on a random forest model RapidEye Sentinel-2. Six scenarios devised considering composition input dataset, was used evaluate accuracy different datasets for each scenario. The hi...

Purpose: To investigate inherent information provided by 18F-FDG PET to ameliorate shortcomings of relying on visual inspection or sole SUV measurement in treatment assessing. Patients and methods: Twelve patients with newly diagnosed NSCLC and treated with combined Chemoradiotherapy (CRT) were involved in this study. We analyzed the percentage variation of gray value in every gray level or on ...

Daun menjadi salah satu daya tarik manusia untuk melakukan kegiatan berkebun atau lain seperti penjualan tanaman karena dari segi bentuk daun yang unik dan karakteristik bermacam-macam. Untuk mengetahui pada jenis dilakukan proses ekstraksi fitur. Tujuan fitur ini bentuk, tekstur, warna,ukuran, nilai digunakan sebagai pembeda antara objek dengan lain. Pada penelitian menggunakan 32 citra daun. ...

In this paper we present a method for segmentation of documents image with complex structure. This technique based on GLCM (Grey Level Co-occurrence Matrix) used to segment this type of document in three regions namely, 'graphics', 'background' and 'text'. Very briefly, this method is to divide the document image, in block size chosen after a series of tests and then applying the co-occurrence ...

In this work a back propagation neural network (BPNN) is used for the segmentation of Meteosat images covering the Iberian Peninsula. The images are segmented in the classes land (L), sea (S), fog (F), low clouds (CL), middle clouds (CM), high clouds (CH) and clouds with vertical growth (CV). The classification is performed from an initial set of several statistical textural features based on t...

This paper developed a CAD (Computer Aided Diagnosis) system based on neural network and a proposed feature selection method. The proposed feature selection method is Maximum Difference Feature Selection (MDFS). Digital mammography is reliable method for early detection of breast cancer. The most important step in breast cancer diagnosis is feature selection. Computer automated feature selectio...

Recently, there has been an increase in the number of hazardous events, such as fire accidents. Monitoring systems that rely on human resources depend on people; hence, the performance of the system can be degraded when human operators are fatigued or tensed. It is easy to use fire alarm boxes; however, these are frequently activated by external factors such as temperature and humidity. We prop...

This paper starts with the local textural information of ultrasound thyroid images. The recent feature extraction methods are presented with the different application areas. The basic objective of this study is to identify and represent the performance of a novel approach for texture characterization of thyroid ultrasound images. The method proposed here should reduce the uncertainty produced b...

This paper presents an evaluation and comparison of the performance of three different feature extraction methods for classification of normal and abnormal patterns in mammogram. Three different feature extraction methods used here are intensity histogram, GLCM (Grey Level Co-occurrence Matrix) and intensity based features. A supervised classifier system based on neural network is used. The per...

The grey level co-occurrence matrix (GLCM) is used in this work for quantitative spatial texture description. The two GLCM metrics, offset and contrast, are used to quantify spatial intensity variation. It is shown that the optimal DIC pattern must possess low critical GLCM offset and high nominal GLCM contrast. A very strong correlation between the critical GLCM contrast and the correlation wi...