Modelling vision angles of optical camera zoom using image processing algorithm

Abstract

A challenge of adding a new feature to the optical properties of a camera is solved in this paper. Image processing gives the possibility to enhance the quality, resolution and details of images fast these days. Within this paper, the introduced algorithm used to determine the vision angles (horizontal and vertical) of a digital camera (Nikon). The quality and efficiency of the camera are evaluated using determine the spatial resolution of the captured images. A scale factor algorithm is used also in this paper. A mathematical model introduced to describe the camera angle vision. This model works with different zoom degrees and different camera-object distances. Thus, a general mathematical equation obtained which describes the real image. The comparisons between the real and resulted images give a strong matching with small error rate.

New algorithms to Enhanced Fused Images from Auto-Focus Images

“…There are different methods within the fusion technique presented and used within this paper. Some of them are used for comparison like Brovey Transform (BT) Algorithm (23), color normalized transformation (24), Local mean matching (LMM), Wavelet Transformation (WT), and High Pass Filter Additive (HPFA) (25). All these methods are compared with the suggested method with mean, contrast, and standard deviation criteria.…”

Feature Extraction in Six Blocks to Detect and Recognize English Numbers

“…However, since heterogeneity in a Fuzzy structure is managed by applying linguistically specified sets, some researches have shown that it is possible specific rule to execute the recognition task based on the membership of a given input to the different defined Fuzzy sets [16]. Fuzzy logic is inherently superior to processing precise results, which is natural for this use [17]. Data treatment is required so that it can be conveniently represented in the Fuzzy laws.…”