Kicad Case Study

All schematic design has been done on Ki Cad. It is an open-source software tool for the creation of electronic schematic diagrams and Printed circuit board (PCB). KiCad represents the ideal tool for projects oriented towards the creation of electronic hardware with an open-source flavour.
KiCad is characterised by an interesting work-flow in which schematic components and footprints are actually two separate entities. The KiCad work-flow is comprised of two main tasks: making the schematic and laying out the board. Both a component library and a footprint library are necessary for these two tasks. Figure schematic and footprint creation work-flow in kicad
Kicad allows you to create a library of part symbols for use in schematic entry.
Then draw nets to make electrical connections between components.
• Bill of Materials
Bill of material is generated automatically using kicad which helps during assembling of board.

COMPONENT FOOTPRINT
There is an extensive footprint library with Kicad, if footprint of required component is not available in the library we can create footprint of that components and add to library. We have created Sascan library in Kicad and loaded the entire components footprint in Sascan library.

SCHEMATIC DESIGN OF PROPOSED SYSTEM SCHEMATIC DESIGN OF LED BOARD

CHAPTER IV
IMPLEMENATION AND RESULTS

4.1 PCB DESIGN AND COMPONENT POPULATION The proposed system PCB design is drawn and components are populated as shown in figure Figure
4.2 Ring LED Board Figure

Main board and LED board interfacing

Sequentially triggering of LEDS Testing

4.2 Image Acquisition

Typical images acquired at R545 nm and R575 nm during clinical study in Oral and Maxillofacial Pathology Department of the Government Dental College (GDC), Trivandrum. Algorithms are developed using MATLAB for the image analysis. Figure Typical images acquired at R545nm and at R575 nm respectively;
4.3 Image
 Image size is 1004 x 1002
 Before the analysis, except the tongue portion other unwanted portion of the both images is cropped using imtool ().
 The ratio of R545 nm / R575 nm of the cropped image is taken to get monochrome image as output.
 Histogram is applied to the Monochrome image in which gives the pixel intensity values.
 Based on the intensity values psuedomapping is assigned.
 The colour coding gives the information about oral lesion discrimination. Oral lesion into blue color (healthy tissue), red color (dysplastic/ pre-malignant) and yellow (malignant tissue) color.

RESULTS:

A) B) C)