This study aims to identify the condition of corn plants based on imagery leaf using gray level co-occurrence matrix (GLCM) method and artificial neural network (ANN) backpropagation. The GLCM is used for extracting features from image corn, whereas ANN backpropagation classification plant features. was done a dataset leaves with four conditions: healthy, spot, blight, rust. Next, are extracted...

Buah Monk merupakan buah asal Cina yang dipercaya memiliki banyak manfaat dan khasiat. termasuk dalam keluarga labu ini sering digunakan sebagai pemanis pengganti gula baik untuk diet hingga penderita diabetes. Memiliki bentuk bulat agak lonjong dengan warna kulit hijau. Setiap ciri menentukan mutu/kualitasnya. Namun, monk segar jarang ditemui di pasaran karena sifatnya cepat membusuk. salah sa...

Mammography is the best method for the early diagnosis of breast cancer. This paper provides an automatic way for the classification of cancer. The image which may be prone to noise is denoised for accurate diagnosis. To have a better outlook at the image it is enhanced using non linear operator function. The tumour which is to be segmented for further investigation is done morphological filter...

Statistical Geometric Features (SGF) have recently been proposed for the classification of image textures. The SGF method is easily extended to use other geometric properties of connected regions. Following a brief review of the method, we propose such an extension to the set of SGF features for the purpose of classifying cervical cell textures. The resulting method proves to be as powerful as ...

An optimal thenar palmprint classification model is proposed in this paper. Firstly, the thenar palmprint image is enhanced using a high-frequency emphasis filter and histogram equalization. Then, from the enhanced image thirteen textural features of gray level co-occurrence matrix (GLCM) are extracted as classification feature vectors. Finally, the SVM classifier is used for classification and...

This paper presents the artificial neural network approach namely Back propagation network (BPNs) and probabilistic neural network (PNN). It is used to classify the type of tumor in MRI images of different patients with Astrocytoma type of brain tumor. The image processing techniques have been developed for detection of the tumor in the MRI images. Gray Level Co-occurrence Matrix (GLCM) is used...

So far, plant identification has challenges for several researchers. Various methods and features have been proposed. However, there are still many approaches could be investigated to develop robust plant identification systems. This paper reports several experiments in using Zernike moments to build foliage plant identification systems. In this case, Zernike moments were combined with other fe...

This study presents a computer algorithm, which consists of four main steps (image acquisition, image pre-processing, nodule candidate detection, and feature extraction) for nodule detection in chest radiographs. Algorithm is applied on small-cell type of lung cancer (SCLC) and non-small-cell type of lung cancer (NSCLC) images. Total 50 images (25 from each category) were used to estimate geome...

Breast cancer is one of the leading cancers among women in developed countries including India. Early diagnosis of the cancer allows treatment which could lead to high survival rate or avoids further clinical evaluation or breast biopsy reducing the unnecessary expenditure. This paper aims to build Artificial Neural Network (ANN) model for detection of breast cancer based on Image Registration ...

This paper uses an analysis of Speeded up Robust Feature (SURF), based on the method of Linear Interpolation for camera distortion calibration, for high-density crowd counting. The eigenvalues are built on the Gray Level Co-occurrence Matrix (GLCM) features and the SURF features. Through the method of linear interpolation, weight values are interpolated to reduce the error, which is caused by c...