The International Journal on the Image 

About: The International Journal on the Image is an academic journal published by Common Ground Research Networks. The journal publishes majorly in the area(s): Photography & Image retrieval. It has an ISSN identifier of 2152-7857. Over the lifetime, 208 publications have been published receiving 942 citations. The journal is also known as: International journal of sport & society & International journal of sport and society: annual review.

Detection of Diseases on Cotton Leaves and its Possible Diagnosis

Abstract: In a research of identifying and diagnosing cotton disease, the pattern of disease is important part in that, various features of the images are extracted viz. the colour of actual infected image, there are so many diseases occurred on the cotton leaf so the leaf colour for different diseases is also different, also there are various other features related to shape of image, also there are different shape of holes are present on the leaf of the image, generally the leaf of infected image have elliptical shape of holes, so calculating the major and minor axis is the major task. The features could be extracted using self organizing feature map together with a back-propagation neural network is used to recognize colour of image. This information is used to segment cotton leaf pixels within the image, now image which is under consideration is well analyzed and depending upon this software perform further analysis based on the nature of this image.

Principal component analysis in medical image processing: a study

Abstract: Principal component analysis (PCA) is a mathematical procedure which uses sophisticated mathematical principles to transform a number of correlated variables into a smaller number of variables called principal components. In PCA, the information contained in a set of data is stored with reduced dimensions based on the integral projection of the dataset onto a subspace generated by a system of orthogonal axes. The reduced dimensions computational content is selected so that the significant data characteristics are identified with little information loss. Such a reduction is an advantage in several fields as for image compression, data representation, etc. It can also be widely used for feature extraction, image fusion, image compression, image segmentation, image registration, de-noising, etc. This paper presents a survey of the applications of PCA in the field of medical image processing. In this study, various medical image application-based PCA results are exhibited to prove its efficiency.

Method for Real Time Text Extraction of Digital Manga Comic

Abstract: Manga is one of popular item in Japan and also in the rest of the world. Hundreds of manga printed everyday in Japan and some of printed manga book was digitized into web manga. People then make translation of Japanese language on manga into other language -in conventional wayto share the pleasure of reading manga through the internet. In this paper, we propose an automatic method for detect and extract Japanese character within a manga comic page for online language translation process. Japanese character text extraction method is based on our comic frame content extraction method using blob extraction function. Experimental results from 15 comic pages show that our proposed method has 100% accuracy of flat comic frame extraction and comic balloon detection, and 93.75% accuracy of Japanese character text extraction.

Offline Signature Verification Using Local Radon Transform and Support Vector Machines

Abstract: In this paper, we propose a new method for signature verification using local Radon Transform. The proposed method uses Radon Transform locally as feature extractor and Support Vector Machine (SVM) as classifier. The main idea of our method is using Radon Transform locally for line segments detection and feature extraction, against using it globally. The advantages of the proposed method are robustness to noise, size invariance and shift invariance. Having used a dataset of 600 signatures from 20 Persian writers, and another dataset of 924 signatures from 22 English writers, our system achieves good results. The experimental results of our method are compared with two other methods. This comparison shows that our method has good performance for signature identification and verification in different cultures.