IJCSIS Papers by kamlesh kumar
—The accuracy and efficiency are two main issues in the context of image retrieval system during ... more —The accuracy and efficiency are two main issues in the context of image retrieval system during searching, indexing and retrieving images from huge databases. In this paper, multi-level color and texture feature extraction has been performed for Content Based Image Retrieval (CBIR) system. The proposed method implements color moment descriptor over Local Binary Patterns (LBP) texture feature. The CBIR system has been designed for Amsterdam Library of texture (ALOT) images. The proposed method has been compared with single color moment descriptor, LBP texture feature and then combined color and texture separately. The experimental results were generated by using MATLAB which shows that accuracy and efficiency of proposed method are considerably higher in terms of overall precision, recall and its retrieval time.
Papers by kamlesh kumar
Indian Journal of Science and Technology
Objectives: Automatic face recognition has been an important area of biometric authentication and... more Objectives: Automatic face recognition has been an important area of biometric authentication and verification system in various applications including crime detection, access control, video surveillance, tracking service and other related area. Methods/Statistical analysis: In this study, we present Grey Level Co-occurrence Matrix (GLCM) over Local Binary Patterns (LBP) named as GOL texture feature technique for face classification. The experiments have been conducted on AT & T Cambridge Laboratory face images also called (ORL-faces) and Georgia Tech (GT-faces) databases respectively. Findings: We performed comparative analysis of GLCM and LBP method separately and results showed that proposed GOL method outperformed in terms of average sensitivity, average specificity, and retrieval time. These findings show efficacy of our proposed system.
International Journal of Advanced Computer Science and Applications
Object detection and tracking with the aid of computer vision is a most challenging task in the c... more Object detection and tracking with the aid of computer vision is a most challenging task in the context of Driver Assistant System (DAS) for vehicles. This paper presents pedestrians detection techique using Haar-Like Features. The main aim of this research is to develop a detection system for vehicle drivers that will intimate them in advance for pedestrian's movement when they are crossing the zebra region or passing nearby to it along the road. For this purpose, dataset of 1000 images have been taken via CCTV camera which was mounted for road monitoring. A Haar based cascade classifiers have been implemented over images. And system is trained for positive (with people) and negative (without people) image samples, respectively. After testing, the obtained results show that it attained 90% accuracy while pedestrian detection. The proposed work provides significant contribution in order to reduce the road accidents as well as ensure the safety measurement for road management.
2014 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing(ICCWAMTIP), 2014
Medical Imaging is currently a hot area of bio-medical engineers, researchers and medical doctors... more Medical Imaging is currently a hot area of bio-medical engineers, researchers and medical doctors as it is extensively used in diagnosing of human health and by health care institutes. The imaging equipment is the device, which is used for better image processing and highlighting the important features. These images are affected by random noise during acquisition, analyzing and transmission process. This condition results in the blurry image visible in low contrast. The Image De-noising System (IDs) is used as a tool for removing image noise and preserving important data. Image de-noising is one of the most interesting research areas among researchers of technology-giants and academic institutions. For Criminal Identification Systems (CIS) & Magnetic Resonance Imaging (MRI), IDs is more beneficial in the field of medical imaging. This paper proposes an algorithm for de-noising medical images using different types of wavelet transform, such as Haar, Daubechies, Symlets and Bi-orthogonal. In this paper noise image quality has been evaluated using filter assessment parameters like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Variance, It has been observed to form the numerical results that, the presentation of proposed algorithm reduced the mean square error and achieved best value of peak signal to noise ratio (PSNR). In this paper, the wavelet based de-noising algorithm has been investigated on medical images along with threshold.
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IJCSIS Papers by kamlesh kumar
Papers by kamlesh kumar