{'fraction_non_alphanumeric': 0.024390243902439025, 'fraction_numerical': 0.0033259423503325942, 'mean_word_length': 5.184931506849315, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Bloodstain Segmentation in Color Images

The identification of bloodstains in color images is critical in some accident investigation cases. A suspected bloodstain segmentation method was proposed in this study. The algorithm transforms the RGB to the YCgCr color space after the image undergoes color histogram equalization. Determination of the decision thresholds (Cg, Cr) is based on the color distribution of the sample images in Cg-Cr plane. To accelerate bloodstain pixel detection, the transformed thresholds are used (Cg¡¦, Cr¡¦). After the bloodstain pixels are detected the fast 8-connected component labeling method is to formulate the clusters. The algorithm was tested by using the 75 images from accident scenes. The results show that su spected bloodstains can be detected successfully, and thus that this approach can be used as the basis for bloodstain identification in color images.