P. Arunachalam¹, N. Janakiraman¹, Junaid Rashid², Jungeun Kim^2,*, Sovan Samanta³, Usman Naseem⁴, Arun Kumar Sivaraman⁵, A. Balasundaram⁶

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2521-2543, 2022, DOI:10.32604/cmc.2022.025339

Abstract In this research work, we proposed a medical image analysis framework with two separate releases whether or not Synovial Sarcoma (SS) is the cell structure for cancer. Within this framework the histopathology images are decomposed into a third-level sub-band using a two-dimensional Discrete Wavelet Transform. Subsequently, the structure features (SFs) such as Principal Components Analysis (PCA), Independent Components Analysis (ICA) and Linear Discriminant Analysis (LDA) were extracted from this sub-band image representation with the distribution of wavelet coefficients. These SFs are used as inputs of the Support Vector Machine (SVM) classifier. Also, classification of PCA + SVM, ICA + SVM,… More >

K. K. Thyagharajan, G. Nirmala^*

Computer Systems Science and Engineering, Vol.41, No.1, pp. 357-371, 2022, DOI:10.32604/csse.2022.020258

Abstract In this paper, copy-move forgery in image is detected for single image with multiple manipulations such as blurring, noise addition, gray scale conversion, brightness modifications, rotation, Hu adjustment, color adjustment, contrast changes and JPEG Compression. However, traditional algorithms detect only copy-move attacks in image and never for different manipulation in single image. The proposed LLP (Laterally linked pixel) algorithm has two dimensional arrays and single layer is obtained through unit linking pulsed neural network for detection of copied region and kernel tricks is applied for detection of multiple manipulations in single forged image. LLP algorithm consists of two channels such… More >