The proposed system identifies the species of the wood using the textural features present in its barks. Each species of a wood has its own unique patterns in its bark, which enabled the proposed system to identify it accurately. Automatic wood recognition system has not yet been well established mainly due to lack of research in this area and the difficulty in obtaining the wood database. In o...

Research in batik image retrieval is still challenging today. In this paper, we present an efficient system for batik image retrieval that combine color and texture features. The proposed approach is based on color auto-correlogram method as color feature extraction method and Gray Level Co-occurrence Matrix (GLCM) method as texture feature extraction method. Firstly, HSV (Hue Saturation Value)...

In this work to provide the information about an object clinically in terms of its size, shape and type of image for this image segmentation and classification are important tool in medical image processing. Ultrasound imaging is the best way to prediction of which type of thyroid is there. In this paper, images were distinguishing in two groups Benign (non-cancerous) and Malignant (cancerous) ...

Background and study aims  Bubbles can impair visualization of the small bowel (SB) mucosa during capsule endoscopy (CE). We aimed to develop and validate a computed algorithm that would allow evaluation of the abundance of bubbles in SB-CE still frames. Patients and methods  Two sets of 200 SB-CE normal still frames were created. Two experienced SB-CE readers analyzed both sets of images twi...

In this paper a method for the automated identification of tree species from images of leaves, bark and needles is presented. The automated identification of leaves uses local features to avoid segmentation. For the automated identification of images of the bark this method is compared to a combination of GLCM and wavelet features. For classification a Support Vector machine is used. The needle...

One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we ...

One of many method for image retrieval is Multi Texton Histogram (MTH) that incorporated feature extraction technique. Though the MTH is able to represent the image very well, it’s still has weaknesses. First, the MTH is only using local features to represent image. Second, in the process of pixel pair detection using texton, there is information missing that caused image representation may deg...

In this paper, images of realworld natural scenes and manmade structures of different depth are taken. With increase in image depth , roughness increases in case of man-made structures whereas natural scene images become smooth, thus reducing the local roughness of the picture. Such kind of specific arrangement produces a particular spatial pattern of dominant orientations and scales that can b...