This study investigates the potential of object-based texture parameters extracted from 15m spatial resolution ASTER imagery for estimating tree size diversity in a Mediterranean forested landscape in Turkey. Tree size diversity based on tree basal area was determined using the Shannon index and Gini Coefficient at the sampling plot level. Image texture parameters were calculated based on the g...

Texture-based computer-aided diagnosis (CADx) of microcalcification clusters is more robust than the state-of-art shape-based CADx because the performance of shape-based approach heavily depends on the effectiveness of microcalcification (MC) segmentation. This paper presents a texture-based CADx that consists of two stages. The first one characterizes MC clusters using texture features from gr...

243  Abstract: Accurate automatic detection and classification of images is very challenging task whether they are medical images or other natural images. This paper presents a hybrid technique for automatic classification of MRI images as well as natural images. The proposed method consists of two stages: feature extraction and classification. In first stage, features are extracted from image...

This paper has a further exploration and study of visual feature extraction. According to the HSV (Hue, Saturation, Value) color space, the work of color feature extraction is fnished, the process is as follows: quantifying the color space in non-equal intervals, constructing one dimension feature vector and representing the color feature by cumulative histogram. Similarly, the work of texture ...

In this paper, we propose a new image segmentation World Academy of Science, Engineering and Technology International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:5, No:5, 2011 427 International Scholarly and Scientific Research & Innovation 5(5) 2011 scholar.waset.org/1999.4/6017 In te rn at io na l S ci en ce I nd ex , C om pu te r an d In fo rm at io n...

Among women, 12% possibility of developing a breast cancer and 3.5% possibility of mortality due to this cause is reported [1]. Nowadays early detection of breast cancer became very important. Mammogram a breast X-ray is used to investigate and diagnose breast cancer. In this paper, authors propose GLCM (Grey Level Co-occurrence Matrix) feature based improved mammogram classification using an a...

This paper presents preliminary results for the classiication of Pap Smear cell nuclei, using Gray Level Co-occurrence Matrix (GLCM) textural features. We outline a method of nuclear segment-ation using fast morphological gray-scale transforms. For each segmented nucleus, features derived from a modiied form of the GLCM are extracted over several angle and distance measures. Linear Discriminant...

This paper presents a novel content based image retrieval (CBIR) system based on Framelet Transform combined with gray level co-occurrence matrix (GLCM).The proposed method is shift invariant which captured edge information more accurately than conventional transform domain methods as well as able to handle images of arbitrary size. Current system uses texture as a visual content for feature ex...

Texture classification co-occurrence matrices rotation invariance digital circles discrete Fourier transform. Grey-level co-occurrence matrices (GLCM) have been on the scene for almost forty years and continue to be widely used today. In this paper we present a method to improve accuracy and robustness against rotation of GLCM features for image classification. In our approach co-occurrences ar...

Huichao Hong, Lixin Zheng, Shuwan Pan Engineering Research Center of Industrial Intelligent Technology and Systems of Fujian Providence College of Engineering,Huaqiao University,Quanzhou, China e-mail: [email protected] Abstract: As in various fields like scientific research and industrial application, the computation time optimization is becoming a task that is of increasing importance because of ...