MATLAB Implementation of Vertical Projection Algorithm for Image Analysis

The vertical projection algorithm is widely used in image processing applications such as character segmentation and object localization. Its core principle involves analyzing pixel distribution along the vertical axis to identify target positions. The MATLAB implementation typically consists of three main stages: image preprocessing, projection calculation, and result analysis.

First, input images require binarization processing to convert them into black-and-white format for efficient pixel statistics. The imbinarize function can be employed with either automatic thresholding (Otsu's method) or manual threshold specification to ensure target regions (like text characters) appear as white foreground objects against a black background. This preprocessing step is crucial for accurate projection calculations.

Next, compute the vertical projection histogram by summing pixel values column-wise across the binarized image. Using MATLAB's sum function with logical indexing (where white pixels equal 1), we generate a vector representing pixel density per column. Peaks in this projection vector typically correspond to vertical regions containing target objects, while valleys indicate potential segmentation boundaries between objects.

Finally, segmentation points are determined through threshold analysis or local minima detection. For instance, the findpeaks function can identify peak intervals, or differential methods can locate sudden drops in projection values. In multi-object scenarios, combining connected-component analysis (using bwconncomp) helps optimize segmentation accuracy by verifying object boundaries.

This algorithm proves particularly effective in OCR preprocessing pipelines, though practitioners should note that uneven illumination or noise interference may distort projection curves. Real-world implementations often incorporate horizontal projection analysis or morphological operations (like imopen) to enhance robustness against such variations.