Wriee code that wil: - Dedermine the seference threahoid value from refing - Use this threshold to segment newing withoul histogram matching. Save the results as newt ngth. - Match newing's histogram to ref teng's histogram. Then use the reference threshold to segrrent the histogramematched crack image. Save the results as matchiegBi. Consider your results. Which segmertation is more apcurate? Noisier? if you were detecting cracks to identify areas of a dam that need repak, would the histogrammatched segmentation be sumficient? Share your thoughts on the forums. Script 0 Image Histogram Matching Histogram matching is useful when you are batch procesing many images and want to apply a common theeshold. This allows you to account for differences in intensity peaks whlle stall avolding the time-consuming process of calculating a new threshold for each image. In this problem, you will predetermine a threshold value and use this threshold and histogram matching to segrnent a new crack image. You will determine a reference threshoid value based on the following image, "ref Ing" (00004.jpg from the Concrete Crack dataset): And apply this threshoid to segment a new image, "newing" (00143.jpg trom the concrete crack dataset), with and without histogram makching. Write code that will