The effect of aliasing on graphic scenes stems from the discretization that must be applied to the scene image. This discretization takes place due to the physical limitation that the pixels impose in the representation of the colors compromising the visual aspect of the created scene. As a result, a reduction in quality and visual attractiveness is achieved. Antialiasing methods were proposed in order to minimize the effects caused by aliasing. They work on color smoothing reducing abrupt variation in certain regions of the scene. Most of these antialiasing methods work in the division of pixels generating new elements, called subpixels that are used for the more precise calculation of the color of a pixel. Despite the visual improvement in the scenes, they become quite costly in terms of memory consumption and processing, which makes it impossible to apply effectively in real-time applications such as simulators or games. An inherent limitation to these methods is that they are designed to act on rasterization of specific figures such as straight lines or special curves. The purpose of this work is to use spatial image filtering methods to create a new generic method that uses the generated pixels to correct the aliasing effect. This approach is based on spatial filtering, which is more efficient in memory utilization and processing. This strategy allows the combination of different geometric transformations to detect different forms of objects. The method groups the enhanced and smoothing filters allied with geometric transformation of rotation to perform operations on the spatial domain of the image.