Title: Enhanced Fundus Images by Using Hybrid Neighbourhood Estimator before Filling with Fuzzy Based Filtering
Authors: Manpreet Kaur and Jagbir Singh Gill
Abstract: Diabetic Retinopathy is an eye disorder that leads to blindness caused by damage in retina. For this reason the exact recognition of vessels become difficult. In order to overcome this difficulty and early detection of eye diseases there are various vessel segmentation techniques. This paper presents a Hybrid Neighbourhood Estimator before Filling (NEBF) with fuzzy based filtering technique which enables us to segment vessels even in low intensity of images. We Firstly extracted the exudates from fundus image then applying NEBF. NEBF is an impainting filter which is used to inpaint exudates so that false positives are reduced in image. The fuzzy based filtering technique is applied based on segmentation. The proposed method is tested on DRIVE database. This provides us with better results over the existing methods even in the case when low depth of images.
Title: Improved Coarse Estimated Atmospheric Veil Algorithm by using Fuzzy Filters and Dark Channel with Large Haze Gradients
Authors: Tanu Mahajan and Jagbir Singh Gill
Abstract: Fog phenomena bring about air flow gentle generating and also decline this awareness involving made from photograph caught in the camera. To increase awareness, air flow gentle evaluation is essential regarding photograph errors removal. As air flow gentle can be quite dazzling, this conventional methods immediately select dazzling p regarding air flow gentle estimation.In this paper improved/hybrid fuzzy filters based haze removal algorithm is proposed. The dark channel prior can automatically extract the global atmospheric light and roughly eliminate the atmospheric veil. To make dark channel prior more effective, the atmospheric veil has been refined by using hybrid fuzzy filters as well as it able to produce a haze free image in more optimistic manner. The use of improved/hybrid fuzzy filters has improved the coarse estimated atmospheric veil by reducing halo artifacts.
Title: Performance Analysis of ANFIS Approach for Effective Selection of Job Applicants at Certain Offered Post
Authors: Rajiv Thapa and Rajni Verma
Abstract: In this work, the ANFIS (Adaptive Neuro-Fuzzy Inference System) is used to the generated Expert system to find job matching for unemployed and also to give the effective selection of job. The dataset which is used to feed into the ANFIS is the data contain the different sets of mix design of different jobs finding. Using ANFIS the error generated by proposed approach is less as compared to FIS(Fuzzy Inference System).