This paper discusses a novel development in estimating the feature of hard lump embedded within a soft tissue with the tactile sensor emulating the major features of a human finger. The aim of this study is to realize precise and quantitative tactile sensing, especially of the stiffness. Since pathology-detection is related to tissue stiffness, stiffness measurement would be of great use to provide insight into disease processes and an aid to diagnosis. When pressed into and scanned over tissue of interest with the tactile sensor proposed, the outputs and variance of the outputs of the tactile sensor depends on the mechanical properties and geometric distribution of the structures within the tissue. The features of interest are the stiffness and the depth of the background tissue and the stiffness, size and location of a hard lump emulating the hard tumor. A finite element model was constructed in order to simulate the tactile process. The analysis was performed on models spanning an experimentally determined range of material properties. By analyzing the simulations in groups, we were able to estimate the tendency of the tissue stiffness, location and size information from tactile sensing. Results show the potential of our approach.