Background: In a light microscope, image acquisition with different component depths is difficult, and there are various approaches for solving this problem. One of the common approaches is Camera Lucida (CL). This method has some disadvantages such as time-consuming, handed problems in painting, causing user boring, and produce gray scale output images. Aims and Objectives: In this study, we purposed a novel-combined hardware and software method. In this article, we try to present an automated method for our designed microscope. Materials and Methods: We have done a project with designed code number 377,694 to design and implement an upgraded light microscope. That project was about automatic movement of a stage with closed-looped control of a servomotor. Furthermore, automated camera catches images in predefined positions. That project has acceptable results in different parts, which encourage us to work on this study. This study help specialist have good fixative of all components in a sample. It is about trying to have useful Lucida Camera (drawing tube) in an automated scheme. Results: This method is an acceptable usual way for microscopic specialists, but with some disadvantages. It is time-consuming and boring that effect on the accuracy of results. Hence, how can be good if automated similar method could be implemented is exciting and affective. This studies idea comes from the basis of manual drawing tube (CL) method. In this experimental study, we have taken 400 handed an image of microorganisms. Captured images are from its whole body or various organs. They have been captured in different z-axis positions of stage, and hence components with different depths could be focused. Each patch checked for its edge strength to choose highest resolutions sub image and reconstruct focused image like a puzzle. This process has been continued for all areas to merge and complete reconstructed image as output. Conclusion: Comparing edge strength with other images and mean square error with manual focused on confirm our method with pleasure outcomes. Furthermore, independent focusing of an internal component in a sample body has been surveyed. It helps to have better resolution in internal selected component for more analysis and replace in its primitive image. This article presents efficient consequences with good accuracy and saving time in process period, which could be useful in different microscopes types and various samples type.

Automating the camera Lucida method which is a standard way for focusing microscopic images is a very challenging study for many scientists. Hence, actually combining hardware and software to automate microscopic imaging systems is one of the most important issues in the field of medicine as well. This idea reduces scanning time and increases the accuracy of user's results in this field. Closed-loop control system has been designed and implemented in the hardware part to move the stage in predefined limits of 15°. This system produces 50 consecutive images from parasites at the mentioned spatial distances in two directions of the z-axis. Then, by introducing our proposed relational software with combining images, a high-contrast image can be presented. This colored image is focused on many subparts of the sample even with different ruggedness. After implementing the closed-loop controller, stages movement was repeated eight times with an average step displacement of 20 μm which were measured in two directions of the z-axis by a digital micrometer. On average, the movement's error was 1 μm. In software, the edge intensity energy index has been calculated for image quality evaluation. The standard camera Lucida method has been simulated with acceptable results based on experts' opinions and also mean squared error parameters. Mechanical movement in stage has an accuracy of about 95% which will meet the expectations of laboratory user. Although output-focused colored images from our combining software can be replaced by the traditional fully accepted Camera Lucida method.